An Indexed Bibliography of Genetic Algorithm Theses

An Indexed Bibliography of Genetic Algorithm Theses compiled by

Jarmo T. Alander Department of Electrical Engineering and Automation University of Vaasa P.O. Box 700, FIN-65101 Vaasa, Finland phone: +358-6-324 8444, fax: +358-6-324 8467

Dedicated to Alan C. Schultz

Report Series No. 94-1-THESES (DRAFT 2009/01/07 14:01 )

available via anonymous ftp: site ftp.uwasa.fi directory cs/report94-1 file gaTHESESbib.pdf

c 1994-2008 Jarmo T. Alander Copyright

Trademarks Product and company names listed are trademarks or trade names of their respective companies.

Warning While this bibliography has been compiled with the utmost care, the editor takes no responsibility for any errors, missing information, the contents or quality of the references, nor for the usefulness and/or the consequences of their application. The fact that a reference is included in this publication does not imply a recommendation. The use of any of the methods in the references is entirely at the user’s own responsibility. Especially the above warning applies to those references that are marked by trailing ’†’ (or ’*’), which are the ones that the editor has unfortunately not had the opportunity to read. An abstract was available of the references marked with ’*’.

Contents 1 Preface 1.1 Your contributions erroneous or missing? 1.1.1 How to cite this report? . . . . . . 1.2 How to get this report via Internet? . . 1.3 Acknowledgement . . . . . . . . . . . . . .

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2 Introduction

1 2 2 2 2 4

3 Statistical summaries 3.1 Publication type . . . . . 3.2 Annual distribution . . . . 3.3 Classification . . . . . . . 3.4 Authors . . . . . . . . . . 3.5 Geographical distribution 3.6 Conclusions and future . .

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5 5 5 5 7 8 8

4 Indexes 4.1 Books . . . . . . . . . 4.2 Journal articles . . . . 4.3 Theses . . . . . . . . . 4.3.1 PhD theses . . 4.3.2 Master’s theses 4.4 Report series . . . . . 4.5 Patents . . . . . . . . 4.6 Authors . . . . . . . . 4.7 Subject index . . . . . 4.8 Annual index . . . . . 4.9 Geographical index . .

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9 9 9 9 9 12 13 13 15 20 27 28

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5 Permuted title index

29

Bibliography

61

Appendixes

91

A Abbreviations

91

B Bibliography entry formats

92

i

List of Tables 2.1

Queries used to extract this subbibliography from the source database.

3.1 3.2 3.3 3.4 3.5

Distribution of publication type. . . . . . . . . . . . . . . . . . Annual distribution of contributions. . . . . . . . . . . . . . . The most popular subjects. . . . . . . . . . . . . . . . . . . . . The most productive genetic algorithm theses authors. . . . . The geographical distribution of the authors working on genetic

B.1 Indexed genetic algorithm special bibliographies available online

ii

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4

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5 5 6 7 8

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95

Chapter 1

Preface “ Living organism are consummate problem solvers. They exhibit a versatility that puts the best computer programs to shame. ” John H. Holland, [1]

The material of this bibliography has been extracted from the genetic algorithm bibliography [2], which when this report was compiled (January 7, 2009) contained 20598 items and which has been collected from several sources of genetic algorithm literature including Usenet newsgroup comp.ai.genetic and the bibliographies [3, 4, 5, 6]. The following index periodicals and databases have been used systematically • A: International Aerospace Abstracts: Jan. 1995 – Sep. 1998 • ACM: ACM Guide to Computing Literature: 1979 – 1993/4 • BA: Biological Abstracts: July 1996 - Aug. 1998 • CA: Computer Abstracts: Jan. 1993 – Feb. 1995 • CCA: Computer & Control Abstracts: Jan. 1992 – Dec. 1999 (except May -95) • ChA: Chemical Abstracts: Jan. 1997 - Dec. 2000 • CTI: Current Technology Index Jan./Feb. 1993 – Jan./Feb. 1994 • DAI: Dissertation Abstracts International: Vol. 53 No. 1 – Vol. 56 No. 10 (Apr. 1996) • EEA: Electrical & Electronics Abstracts: Jan. 1991 – Apr. 1998 • EI A: The Engineering Index Annual: 1987 – 1992 • EI M: The Engineering Index Monthly: Jan. 1993 – Apr. 1998 (except May 1997) • Esp@cenet patents – Apr. 2002 • IEEE: IEEE and IEE Journals – Fall 2002 • N: Scientific and Technical Aerospace Reports: Jan. 1993 - Dec. 1995 (except Oct. 1995) • NASA NASA ADS www bibliography database: – Dec. 2002 • P: Index to Scientific & Technical Proceedings: Jan. 1986 – Dec 1999 (except Nov. 1994) • PA: Physics Abstracts: Jan. 1997 – June 1999 • PubMed: National Library of Medicine Jan. 2000 – Oct. 2000 • SPIE Web The International Society for Optical Engineering – June 2002 1

2

1.1

Genetic algorithm theses

Your contributions erroneous or missing?

The bibliography database is updated on a regular basis and certainly contains many errors and inconsistences. The editor would be glad to hear from any reader who notices any errors, missing information, articles etc. In the future a more complete version of this bibliography will be prepared for the genetic algorithm theses research community and others who are interested in this rapidly growing area of genetic algorithms. When submitting updates to the database, paper copies of already published contributions are preferred. Paper copies (or ftp ones) are needed mainly for indexing. We are also doing reviews of different aspects and applications of GAs where we need as complete as possible collection of GA papers. Please, do not forget to include complete bibliographical information: copy also proceedings volume title pages, journal table of contents pages, etc. Observe that there exists several versions of each subbibliography, therefore the reference numbers are not unique and should not be used alone in communication, use the key appearing as the last item of the reference entry instead. Complete bibliographical information is really helpful for those who want to find your contribution in their libraries. If your paper was worth writing and publishing it is certainly worth to be referenced right in a bibliographical database read daily by GA researchers, both newcomers and established ones. For further instructions and information see ftp.uwasa.fi/cs/GAbib/README.

1.1.1

How to cite this report?

You can use the BiBTEX file GASUB.bib, which is available in our ftp site ftp.uwasa.fi in directory cs/report94-1 and contains records for GA subbibliographies for citing with LATEX/BibTEX.

1.2

How to get this report via Internet?

Versions of this bibliography are available via anonymous ftp or www from the following site: media ftp

country Finland

site ftp.uwasa.fi

directory /cs/report94-1

file gaTHESESbib.pdf

The directory also contains some other indexed GA bibliographies shown in table B.1. In case you do not find a proper one please let us know: it may be easy to tailor a new one.

1.3

Acknowledgement

The editor wants to acknowledge all who have kindly supplied references, papers and other information on genetic algorithm theses literature. At least the following GA researchers have already kindly supplied their complete autobibliographies and/or proofread references to their papers: Dan Adler, Patrick Argos, Jarmo T. Alander, James E. Baker, Wolfgang Banzhaf, Helio J. C. Barbosa, Hans-Georg Beyer, Christian Bierwirth, Peter Bober Joachim Born, Ralf Bruns, I. L. Bukatova, Thomas Bäck, Chhandra Chakraborti, Nirupam Chakraborti, David E. Clark, Carlos A. Coello Coello, Yuval Davidor, Dipankar Dasgupta, Marco Dorigo, J. Wayland Eheart, Bogdan Filipiˇc, Terence C. Fogarty, David B. Fogel, Toshio Fukuda, Hugo de Garis, Robert C. Glen, David E. Goldberg, Martina Gorges-Schleuter, Hitoshi Hemmi, Vasant Honavar, Jeffrey Horn, Aristides T. Hatjimihail, Heikki Hyötyniemi Mark J. Jakiela, Richard S. Judson, Bryant A. Julstrom, Charles L. Karr, Akihiko Konagaya, Aaron Konstam, John R. Koza, Kristinn Kristinsson, Malay K. Kundu, D. P. Kwok, Jouni Lampinen, Jorma Laurikkala, Gregory Levitin, Carlos B. Lucasius, Timo Mantere, Michael de la Maza, John R. McDonnell, J. J. Merelo, Laurence D. Merkle, Zbigniew Michalewics, Melanie Mitchell, David J. Nettleton, Volker Nissen, Ari Nissinen, Tatsuya Niwa, Tomasz Ostrowski, Kihong Park, Jakub Podgórski, Timo Poranen, Nicholas J. Radcliffe, Colin R. Reeves, Gordon Roberts, David Rogers, David Romero, Sam Sandqvist, Ivan Santibán ˜ez-Koref, Marc Schoenauer, Markus Schwehm, Hans-Paul Schwefel, Michael T. Semertzidis, Davil L. Shealy, Moshe Sipper, William M. Spears, Donald S. Szarkowicz, El-Ghazali Talbi, Masahiro Tanaka, Leigh Tesfatsion, Peter M. Todd,

Acknowledgement

3

Marco Tomassini, Andrew L. Tuson, Kanji Ueda, Jari Vaario, Gilles Venturini, Hans-Michael Voigt, Roger L. Wainwright, D. Eric Walters, James F. Whidborne, Stefan Wiegand, Steward W. Wilson, Xin Yao, Xiaodong Yin, and Ljudmila A. Zinchenko. The editor also wants to acknowledge Elizabeth Heap-Talvela for her kind proofreading of the manuscript of this bibliography and Tea Ollanketo and Sakari Kauvosaari for updating the database. Prof. Timo Salmi and the Computer Centre of University of Vaasa is acknowledged for providing and managing the online ftp site ftp.uwasa.fi, where these indexed bibliographies are located.

Chapter 2

Introduction “Many scientist, possibly most scientist, just do science without thinking too much about it. They run experiments, make observations, show how certain data conflict with more general views, set out theories, and so on. Periodically, however, some of us—scientists included—step back and look at what is going on in science.” David L., Hull, [7]

The table 2.1 gives the queries that have been used to extract this bibliography. The query system as well as the indexing tools used to compile this report from the BiBTEX-database [8] have been implemented by the author mainly as sets of simple awk and gawk programs [9, 10]. string PHDTHESIS MASTERSTHESIS

field citeKey citeKey

class PhD thesis Master etc thesis

Table 2.1: Queries used to extract this subbibliography from the source database.

Hint

4

Chapter 3

Statistical summaries 3.2

This chapter gives some general statistical summaries of genetic algorithm theses literature. More detailed indexes can be found in the next chapter.

Table 3.2 gives the number of genetic algorithm theses papers published annually. The annual distribution is also shown in fig. 3.1. The average annual growth of GA papers has been approximately 40 % during late 70’s - early 90’s.

References to each class (c.f table 2.1) are listed below: • Master etc thesis 189 references ([11]-[199])

year 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 total

• PhD thesis 387 references ([200]-[586]) Observe that each reference is included (by the computer) only to one of the above classes (see the queries for classification in table 2.1; the textual order in the query gives priority for classes).

3.1

Publication type

This bibliography contains published contributions including reports and patents. All unpublished manuscripts have been omitted unless accepted for publication. In addition theses, PhD, MSc etc., are also included whether or not published somewhere. Table 3.1 gives the distribution of publication type of the whole bibliography. Observe that the number of journal articles may also include articles published or to be published in unknown forums. type journal article proceedings article PhD thesis MSc thesis total

Annual distribution

number of items 1 1 387 189 578

items 2 2 0 2 1 2 0 2 5 2 5 7 12 23 49 45 35 32 12 33 9 5

year 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

items 0 0 4 3 3 1 2 2 4 5 8 8 21 46 70 24 27 25 17 13 6 4 578

Table 3.2: Annual distribution of contributions.

3.3

Classification

Every bibliography item has been given at least one describing keyword or classification by the editor of this bibliography. Keywords occurring most

Table 3.1: Distribution of publication type.

5

6


are shown in table 3.3.

Total engineering evolution strategies optimization parallel GA neural networks analysing GA control implementation genetic programming machine learning comparison proteins medicine image processing signal processing hybrid CAD scheduling robotics TSP spectroscopy chemistry simulation manufacturing protein folding physics routing quantum computing graphs classifier systems testing software testing optics filters economics shape design evolution coding classification system identification electronics electromagnetics design biology VLSI others

578 80 42 41 37 35 30 27 25 22 21 21 20 17 17 16 16 16 15 14 14 13 12 11 11 10 10 8 8 8 8 7 7 7 7 7 6 6 6 6 5 5 5 5 5 5 1123

Table 3.3: The most popular subjects.

Authors

3.4

7

Authors

Table 3.4 gives the most productive authors.

total number of authors 3 authors 19 authors 538 authors

560 3 2 1

Table 3.4: The most productive genetic algorithm theses authors.

6Genetic algorithm theses

ccc c ccc c c 1000 c c c number of papers c c (log scale) c cccc 100 cc s cc c ss s ss s c sss c ss s c cc s s s c cc cccc 10 s sss cc c ss c s ss c c s s s c cc ss c cs sc s s sss s 1c cc s s 1960

2009/01/07

1970

1980 YEAR

1990

2000

Figure 3.1: The number of papers applying genetic algorithm theses (•, N = 578 ) and total GA papers (◦, N = 20598 ). Observe that the last few years are most incomplete in the database.

8

3.5


Geographical distribution

Table 3.5 gives the geographical distribution of authors, when the country of the author was known. Over 80% of the references of the GA source database are classified by country. 2009/01/07

country Total United States Finland Germany United Kingdom Canada France Sweden The Netherlands Australia Austria Belgium China Brazil Israel Italy Spain Denmark Norway Poland South Korea Others

special n % 569 100.00 285 50.09 80 14.06 78 13.71 35 6.15 16 2.81 8 1.41 7 1.23 7 1.23 6 1.05 5 0.88 5 0.88 4 0.70 3 0.53 3 0.53 3 0.53 3 0.53 2 0.35 2 0.35 2 0.35 2 0.35 15 2.68

comparison δ[%] ∆[%] +22.35 +10.31 +6.74 −4.09 +1.28 −1.12 +0.74 +0.22 −1.42 +0.27 +0.04 −4.10 −0.33 −0.08 −2.35 −1.17 +0.08 +0.21 −0.55 −1.95 −4.34

+81 +275 +97 −40 +84 −44 +151 +22 −57 +44 +5 −85 −38 −13 −82 −69 +30 +150 −61 −85 −62

all N 19420 5388 729 1354 1988 297 491 95 197 480 118 163 933 167 118 559 330 53 28 175 446 1361

% 100.00 27.74 3.75 6.97 10.24 1.53 2.53 0.49 1.01 2.47 0.61 0.84 4.80 0.86 0.61 2.88 1.70 0.27 0.14 0.90 2.30 7.02

Table 3.5: The geographical distribution of the authors working on genetic algorithm theses (n) compared (δ and ∆) to all authors in the field of GAs (N ). In the comparison column: δ% = %special−%all and nNT otal ∆ = (1 − N nT otal ) × 100%. ∆ is the relative (%) deviation from the expected number of special papers. Observe that joint papers may have authors from several countries and that not all authors have been attributed to a country.

3.6

Conclusions and future

The editor believes that this bibliography contains references to most genetic algorithm theses contributions upto and including the year 1998 and the editor hopes that this bibliography could give some help to those who are working or planning to work in this rapidly growing area of genetic algorithms.

Chapter 4

Indexes 4.1

Books

Brunel University,

[445]

California Institution of Technology,

The following list contains all items classified as books.

Cardiff University,

[429]

Carleton University,

[353]

[307]

Carnegie Mellon University,

[254, 320]

Carnegie-Mellon University,

[458]

• none

Case Western Reserve University,

4.2

Catholic University of Nijmegen,

Journal articles

Central Queensland University,

The following list contains the references to every journal article included in this bibliography. The list is arranged in alphabetical order by the name of the journal.

[407] [379]

Chinese University of Hong Kong, City University,

[346]

Clemson University,

[425]

Colorado State University,

IEEE Transactions on Speech and Audio Processing, [234]

4.3

[242, 325]

Theses

The following two lists contain theses, first PhD theses and then Master’s etc. theses, arranged in alphabetical order by the name of the school.

[271]

[328, 330, 467, 538, 569]

Columbia University,

[247, 308, 560]

Cornell University,

[403, 454]

Drexel University,

[375]

Duke University,

[204]

ETH,

[393]

Ecole Centrale de Lyon, [333] Ecole Nationale Sup´ erieure d’Arts et M´ etiers de Bourdeaux, [213]

Ecole Normale Superieure de Lyon,

4.3.1

Eidgen¨ ossische Technische Hochschule Z¨ urich,

PhD theses

?,

[200]

Academy of Sciences,

[578]

Florida Institute of Technology,

George Mason University,

Boston University, Brandeis University,

[364]

[399, 427]

Georgia Institute of Technology, Gesamthochschule Wupperthal,

[248, 250, 261, 269, 345]

[246, 272] [438]

Brno University of Technology, Brown University,

[251]

[452]

[415]

Florida International University,

Air Force Instutute of Technology, Arizona State University,

[329]

HAB Weimar,

[471]

Harvard University,

[341, 541]

[253, 480] [508]

Helsinki University of Technology,

[214, 230, 238, 240, 268, 273, 282, 284, 288, 292, 376, 398, 409, 419, 431, 449, 451]

[241]

Helsinki University of Technology?,

[201]

9

[430]

10


Hong Kong Polytechnic University, Humboldt-Universit¨ at zu Berlin, Illinois Institute of Technology, Imperial College for Science,

Rutgers University,

[264]

[423]

Seoul National University,

[475]

Stanford University,

[202, 312]

[327]

[354, 387, 434, 527, 543]

State University of New York at Binghamton,

[487]

Indiana University,

[534]

State University of New York at Buffalo,

Institut Imag,

[294]

Stockholm University,

Instituto Nacional de Pesquisas Espaciais, Iowa State University,

Syracuse University,

[388]

Katholic University of Leuven,

Katholieke Universiteit Nijmegen, Kungliga Tekniska h¨ ogskolan,

Technical University of Clausthal,

[357]

[290]

Texas A and M University,

Lappeenranta University of Technology,

[413]

[209, 235]

[372]

[304]

The Ohio State University,

[459, 463, 512]

Louisiana State University of Agricultural and Mechanical College, [473]

The Pennsylvania State University,

Massachusetts Institute of Technology,

The Scripps Research Institute, The University of Alabama,

New Mexico State University,

[461, 579]

[581]

North Carolina State University,

[549]

The University of Iowa, [526, 572]

[220, 347]

Norges Teknisk-Naturvitenskapelige Universitet,

[224]

[426]

The University of Connecticut,

[476]

[243]

[245, 344]

North Dakota State University of Agriculture and Applied Sciences, [478, 494, 522, 575]

The University of Manitoba,

[237, 295]

The University of Memphis,

[300, 311]

The University of Michigan,

[343]

The University of Oklahoma, The University of Sydney,

[513]

[285]

The University of Texas at Arlington,

Ohio State University,

[289]

The University of Texas at Austin,

Ohio University,

[377]

The University of Tulsa, [298]

Old Dominion University,

[316, 447, 532, 583]

[352]

The University of Arizona,

[402, 564]

New Jersey Institute of Technology,

New York University,

[255, 355]

[450]

Mississippi State University,

[469, 505, 506, 510, 520,

Texas A&M University, [361] Texas Tech University,

[286, 291, 384]

Michigan State University,

[437]

533, 535, 556, 557, 566, 567]

L’Universite des Sciences et Technologiques de Lille,

McGill University,

[382, 435]

Technische Universit¨ at der Berlin,

[395]

[265]

[256, 336]

Tampere University of Technology,

Kansas State University, [358]

Louisiana State University,

[406]

Swedish University of Agricultural Sciences,

[418]

[359]

[296, 392]

[206]

[444]

[207, 313, 368, 391]

The University of Utah, [342, 521]

Oregon Graduate Institute of Science and Technology, [561]

The University of Wisconsin - Madison,

Oregon State University, [390]

Tulane University,

[373, 460]

Oxford University,

Uninversity of Nevada,

[203]

[323, 350]

[529]

Politechnico di Milano, [490]

Universidad Polit´ ecnica de Madrid,

[315]

Politechnika Warszawska,

Universite Catholoques de Louvain,

[326]

[369]

Polytechnic University,

[331, 483]

Universite de Montreal, [260]

Purdue University,

[518]

University College,

[536]

University Exeter,

[453]

Rensselaer Polytechnic Institute, [222, 244, 263, 462, 548, 555]

University of Aarhus,

[229]

Rijksuniversiteit Groningen,

[228]

University of Adelaide,

[274]

Ruhr-University of Bochum,

[412]

University of Alabama, [489, 524, 525, 550, 577]

Queen’s University at Kingston,

Ruhruniversit¨ at Bochum,

[509]

[411]

University of Alabama at Birmingham,

[442]

PhD theses

11

University of Alabama in Huntsville,

[205, 303]

University of Nevada,

[216]

University of Alberta,

[477, 528]

University of New Hamshire,

University of Arizona,

[332]

University of New Mexico,

University of Bath,

[374]

University of North Carolina at Chapel Hill,

University of Bonn,

[468, 530]

University of North Carolina at Charlotte,

University of California, [210, 270, 297, 305, 314, 389, 394, 397, 432, 515, 551]

University of California at San Diego, University of Cambridge,

[495]

[455]

University of Central Florida,

[417]

[370]

University of Oklahoma, [386] University of Oulu,

[275]

University of Paris 7,

[321]

University of Pennsylvania,

[232, 309, 420]

University of Dortmund, [408, 433, 486, 501]

University of Pittsburgh, [448, 516, 562]

University of Durham,

University of Pretoria,

[586]

University of Edinburgh, [416, 446, 553]

University of Reading,

[233, 421, 466]

University of Erlanger-N¨ urnberg,

University of Rhode Island,

[365]

[349]

[217]

University of Rochester, [405]

[348]

University of Extremadura,

University of Sao Paulo, [436]

[225]

University of Florida,

[227, 422, 479, 570]

University of Sheffield,

University of Georgia,

[385]

University of South Florida,

University of Glamorgan, University of Granada,

[366] [239]

University of Southern California,

[218, 378]

University of Stirling,

[400]

University of Strathclyde,

University of Helsinki,

[223, 279, 563]

University of Surrey,

University of Houston,

[546]

University of Tampere, [226, 280]

[383]

University of Illinois at Chicago,

[584] [310, 363, 367,

552, 571] [339, 485]

[540]

University of London,

[380]

[410]

University of Turku,

[208, 258, 277, 283, 439, 441]

University of Vaasa,

[221, 257, 287, 440]

University of Victoria,

[293]

University of Washington,

University of Karlsruhe, [215] University of Limburg,

[542]

University of Tennessee, [504]

University of Illinois at Urbana-Champaign, University of Iowa,

[337]

[507]

University of Heidelberg, [456, 502]

University of Huddersfield,

[360, 481, 582]

University of Waterloo, [340] University of West Australia,

[211]

University of Louisville, [252, 338, 428]

University of York,

University of Maryland, [276]

University of the West of England,

[219, 424]

University of Maryland College Park,

[299]

Universit¨ at Dortmund,

University of Massachusetts Amherst,

[266]

Universit¨ at Erlangen-N¨ urnberg,

[236]

[317, 335]

University of Michigan, [212, 234, 259, 404, 464, 470, 474, 482,

Universit¨ at Hildesheim, [371]

488, 496, 497, 498, 499, 500, 503, 511, 514, 523, 537, 544, 547, 558, 559, 574, 580]

Universit¨ at der Bremen, [472]

[401]

University of Minnesota, [443, 492]

Universit¨ at-Gesamthochschule Essen,

University of Missouri,

Universit´ e Catholique de Louvain,

[306, 414]

University of Missouri - Rolla,

[319, 322, 491, 493, 554]

University of Montana, [519] University of Montpellier II,

[568]

University of Paris XII, [539]

[301]

University of Cincinnati, [318, 334, 576]

University of Essen,

[517]

[267]

[531]

[381]

Universit´ e de Paris VI,

[362]

Utah State University,

[249, 262, 351, 356]

Vanderbilt University,

[465, 545, 565]

12


Virginia Polytechnic Institute and State University,

[278,

McGill University,

[114]

Monash University,

[80]

281, 484, 585]

Wayne State University, [302, 324, 457] National Chung Cheng University, Yale University,

l’Institut National Polytechnique de Grenoble, ´ Ecole Polytechnique F´ ed´ erale de Lausanne,

[573]

[231]

National Sun Yat-sen University,

[36]

National University of Singapore,

[77]

Naval Postgraduate School,

total 387 thesis in 208 schools

4.3.2

Master’s theses

This list includes also “Diplomarbeit”, “Tech. Lic. Theses”, etc.

[137, 150, 179]

Oxford University,

[164]

Penn State University,

[18]

Rice University,

[69]

Simon Fraser University, [41] Tampere University of Technology, Technical University of Vienna,

?,

[78]

Aarhus University,

[50]

[57]

[13, 102]

Technion - Israel Institute of Technology, Technische Hochschule Darmstadt,

Academy of Sciences of the USSR,

[121]

Air Force Institute of Technology,

[23, 47, 60, 128, 129, 163,

Technische Universit¨ at Wien,

169] [124]

Bergische Universit¨ at,

[142]

[53]

[173]

Technische Universit¨ at der Berlin, Technischen Universit¨ at Berlin,

[130, 140, 157, 167, 180,

Brigham Young University,

[40]

The Hebrew University of Jerusalem,

Blekinge Institute of Technology,

[24]

The University of Alabama,

[89] [73]

Chung Yuan Christian University,

[31]

University of Alberta,

[63]

[81]

University of British Columbia,

College of Engineering and Mineral Resources,

[34]

[171]

[132, 153]

University of California at San Diego, 177, 182, 189, 194, 197, 198]

University of East Anglia,

Eindhoven University of Technology,

University of Edinburgh, [64, 71, 75, 133]

[195]

[115]

[51]

[21] [100]

[187, 188]

Helsinki University of Technology,

[11, 12, 15, 16, 17, 19, 20, 22, 27, 28, 30, 35, 37, 39, 49, 54, 59, 93, 101, 103, 109]

Hochschule der Bundeswehr M¨ unchen, Instituto Superior Tecnico,

KASIST,

[175]

[105]

Johannes Kepler Universit¨ at,

[134]

[192]

Lappeenranta University of Technology,

[26]

[29]

[44, 119]

Lund Institute of Technology,

University of Exeter,

[158]

University of Florence,

[117]

University of Genova?,

[45]

University of Georgia,

[32, 139]

University of Glasgow,

[98]

University of Helsinki,

[87, 94, 111]

University of Idaho,

[136, 145]

University of Illinois at Urbana-Champaign,

King Fahd University of Petroleum & Minerals,

Leiden University,

[149]

University of Erlangen and The University of Tennessee,

Fernuniversit¨ at Gesamthochschule in Hagen, George Mason University,

[135]

University of Dortmund, [118, 127, 141, 151, 154, 160, 165, 170,

Conservatoire National des Artes et Metiers Centre Regional Associe de Grenoble, [123]

Federal University of Parana,

[55]

University of Alabama, [125, 174, 178]

Case Western Reserve University,

FU Berlin,

[86]

183, 190, 196]

Auburn University,

Concordia University,

[72]

[396]

University of Kuopio,

[96]

University of London,

[185]

University of Manchester,

[172]

Marii Curie-Sklodowskiej University of Lublin, Massachusetts Institute of Technology,

University of Industrial Arts Helsinki,

[25]

[33, 67, 79, 91]

University of Miami,

[112]

[48]

University of Missouri - Rolla,

[162]

[14]

[76, 168]

Report series

13

University of Nebraska-Lincoln,

4.5

[61]

University of Newcastle Upon Tyne,

[56]

University of Newcastle upon Tyne,

[92]

University of North Carolina at Charlotte, University of Oslo,

[148, 191]

University of South Australia,

• none [90]

University of Tampere, [88] University of Tennessee, [155] University of Tulsa,

[122, 156, 184, 199]

University of Turku,

[97, 104]

University of Twente,

[147]

University of Ume˚ a,

[131]

University of Utrecht,

[66]

University of Vaasa,

[42, 84, 85, 95, 99, 106, 107, 108, 110]

University of Virginia,

[120, 143]

University of Wales,

[161]

Universit¨ at Bonn,

[166]

Universit¨ at Erlangen-N¨ urnberg, Universit¨ at Kaiserslautern,

[43, 52, 58, 62, 65, 186]

[144]

[181]

Universit¨ at Oldenburg, [113] Universit¨ at Siegen,

[126]

Universit¨ at Stuttgart,

[152]

Universit¨ at W¨ urzburg,

[46]

Universit¨ at der Bremen, [68] Vanderbilt University,

[176, 116, 159]

Victoria University of Wellington,

[146]

Vienna University of Economics and Business Admimistration, [82] Wayne State University, [138] Worchester Polytechnic Institute,

[83]

Wright-Patterson AFB, [70] total 188 thesis in 102 schools

4.4

The following list contains the names of the patents of genetic algorithm theses. The list is arranged in alphabetical order by the name of the patent.

[38]

University of Paderborn, [193]

Universit¨ at M¨ unchen,

Patents

Report series

The following list contains references to all papers published as technical reports. The list is arranged in alphabetical order by the name of the institute.

14


Authors

4.6

15

Authors

The following list contains all genetic algorithm theses authors and references to their known contributions.

Ablay, Paul,

Berke, W.,

[456]

Abu Zitar, Raed Abdullah,

[457]

[469]

Cavicchio, D. J.,

Bethke, A. D.,

[470]

Cesare, Mark Anthony, [483]

[482]

Ackley, David H.,

[458]

Bevan, Jeffrey Spence,

[206]

Cetin, Onur L.,

[259]

Adewuya, A. A.,

[79]

Beyer, Hans-Georg,

[471]

Chan, Shun Heng,

[264]

Chang, Chun-Shi,

[296]

Agnew, Kelly Kathleen, [207]

Beyer, Markus,

[53]

Ahmad, Sabbir U.,

Bhat, Ajita Atul,

[385]

Bierwirth, Christian,

[472]

[293]

Chapman, Christopher Neal, Chatroux, Thierry,

Ahuactzin, Juan-Manuel,

[294]

[200]

[123]

Chemishkian, Sergey Y., [426] Alander, Jarmo T.,

[230, 111]

Birchfield, David Andrew,

Alfken,

[113]

Bitterman, Thomas A., [473]

Al-Harkan, Ibrahim,

[386]

Blackburn, Jason Kenna,

Altman, Erik R.,

[114]

Boers, Egber J. W.,

Alvers, M.,

[115]

Andrade Filho, Antonio Carlos Bittencourt de, [387] Angeline, Peter J.,

[247]

Chen, I.-Ming,

[307]

Chidambaram, Rama,

[261]

Chincarini, A.,

[45]

[119]

Choy, Wing Yiu,

[450]

Booker, Lashon B.,

[474]

Chu, Lon-Chan,

[310]

Born, Joachim,

[475]

Chung, Jinpyung,

[255]

Borst, Marko V.,

[44]

Chung, You Chung,

[216]

Bortolot, Zachary J.,

[281]

Clark, Kevin Patrick,

[394]

Clayton, John Morris,

[253]

Clement, Stuart J.,

[90]

[286]

[459]

Ankenbrandt, Carol Ann,

[460]

Bounsaythip, Catherine, [413] Annaiyappa, Pradeepkumar V., [461] Areibi, Shawki,

[340]

Awadh, Bahaa,

[295]

Ayachi, Naufel, Ayala-Cruz, Jorge, B¨ ack, Thomas, Bagley, J. D., Baker, James Edward,

Bowden, Royce O.,

[476]

Bower, Michael Jason,

[397]

Br¨ aysy, Olli,

[221, 106]

Brem, Rachel Beth,

[210]

Bright, M. S.,

[429]

Brill, Frank Z.,

[120]

Cormier, Denis Roger,

Brindle, A.,

[477]

Cowgill, Marcus Charles, [484]

[43] [462] [335] [464] [116, 465]

Bromberg, Pamela Sharon, Ball, N. R.,

[466]

Ballerini, Lucia,

[117]

[237]

Coello Coello, Carlos A., [373] Collins, Robert James,

[551]

Congdon, Clare Bates,

[343]

Cooper, Mark Gary,

[297]

Corcoran, III, Arthur Leo,

[298]

[344]

Crossley, William A.,

[345] [46]

Brooks, Richard R.,

[384]

Dabs, Tanja,

Brown, Willie G.,

[324]

Daniels, Douglas Stephen,

[301]

[224]

Bangalore, Shanthamallikarjuna Shivappa, [377]

Browne, David G.,

[80]

Davern, James John,

Bank van der, Dirk Johannes,

Bukatova, Innesa L.,

[121]

Davidor, Yuval,

[487]

Davis, Thomas Elder,

[570]

Day, Richard O.,

[23, 23]

Deb, Kalyanmoy,

[125, 489]

DeJong, R. J.,

[78]

Demerling, C.,

[126]

Barash, Danny,

[586]

[432]

Burton, Anthony Richard,

[410]

Baresel, Andr´ e,

[40]

Burton, Scott Andrew,

[263]

Bastin, Gary Lee,

[415]

Cai, J.,

[348]

Beaty, Steven J.,

[467]

Calsamiglia, John,

[223]

Becker, Rainer,

[468]

Canpolat, Necati,

[390]

Depping, J¨ urgen,

[127]

Cantwell, Gregory W.,

[249]

Dewey, John,

[32]

[291]

Dick, Scott H.,

[239]

Diveux, T.,

[213]

Dorigo, Marco,

[490]

Beeson, Nicholas Welborn,

[341]

Behr, Stephen-Marcus,

[118]

Cao, Hua,

Bentley, Peter J.,

[383]

Carlson, Susan Elizabeth,

Bergholm, Ville,

[288]

Caskey, Kevin Richard, [481]

[480]

16

Drain, David Charles,


[248]

Gaulke, R. L.,

[70]

Hemker, Andreas,

[508]

[304]

Hermadi, Irman,

[26]

Heß, Axel,

[144]

[434]

Hicklin, Joseph F.,

[145] [509] [258, 97]

Draney, Rodrick Kimball,

[262]

Giddens, Terri,

Dunkelberg, Jr., John S.,

[83]

Gillies, Andrew McGilvary,

Duponcheele, George,

Gilman, Alexander,

[374]

[498]

Durant, E. A.,

[234]

Glover, David E.,

[485]

Hilgers, P.,

Durant, Eric A.,

[234]

Goldberg, David E.,

[499]

Hirvensalo, Mika,

Dymek, A.,

[128]

Goldfarb, Heidi B.,

[250]

Ho, Lap-Wah Lawrence, [396]

Edmondson, L. Vincent, [491]

Golovkin, Igor E.,

[203]

Hobbs, Matthew F.,

[146]

Eggert, H.,

[130]

Gonzalez, Carlos,

[122]

H¨ ofler, A.,

[510]

Elfwing, Stefan,

[290]

Gonz´ alez-Hern´ andez, Luis F.,

Hollstien, R. B.,

[511]

Elketroussi, Mehdi,

[492]

Goodman, E. D.,

[500]

Holmes, John H.,

[375]

Elmer, B. S.,

[493]

Gordon, Edward O.,

[129]

Hornby, Gregory S.,

[81]

[328]

H¨ orner, Helmut,

[82]

Gorges-Schleuter, Martina, [141, 501]

House, Randy lee,

[306]

Eloranta, Timo,

Gordon, Vahl Scott,

[88]

Emer, Maria Claudia F. P.,

[21]

[71]

Ericson, Christer,

[131]

Gottlieb, Jens,

[437]

Hoyweghen, Clarissa van,

Evans, Neal Crawford,

[442]

Graham, Paul S.,

[89]

Huijsen, W. O.,

[147]

Evertsson, Gustav,

[24]

Grand, Scott Michael Le,

HuiqingJin,

[276]

Ezzell, Gary Allen,

[302]

Gr¨ onroos, Marko A.,

[104]

Hung, Shih-Lin,

[512]

Fahl, B.,

[68]

Groot, Claas de,

[502]

Hussein, Yasser A.,

[269]

Hutt, B. D.,

[233]

Huttunen, Heikki,

[435]

Hwang, Kuo-Yen,

[521]

Hwang, Wen-Ruey,

[579]

Ikonen, Ilkka,

[428]

Ilvonen, Mikko,

[22]

Jacob, Christian,

[349]

[532]

Fang, Hsiao-Lan,

[133]

Groß, M.,

[535]

Feichtel, R.,

[134]

Gross, Hans-Gerhard,

[218]

Fennel, Theron Randy,

[303]

Grosso, Paul Bryant,

[503]

Ferguson, Bradley,

[274]

Gruau, Fr´ ed´ eric C.,

[329]

Fernandez, Jaime J.,

[69]

Gu∂mundsson, Mark´ us, [48]

[246]

Fernandez-de-Vega, F., [225]

Guo, Zhichao,

[504]

Ficek, Rhonda Janes,

[494]

Gurkan, Damla,

[202]

Fogel, David B.,

[135, 495]

Haataja, Juha,

[49]

Fonseca, Carlos M.,

[366]

Hahn, S.,

[142]

Janikow, Cezary Z.,

[517]

Forrest, Stephanie,

[496]

Halliday, Jonathan,

[92]

Jensen, Eric Dean,

[518]

Frantz, D. R.,

[497]

H¨ am¨ al¨ ainen, Timo,

[382]

Jenssen, Mikkel T.,

[229]

Fredriksson, Kimmo,

[94]

Hampel, C.,

[506]

James,

Adrienne

Claire

Nwando,

[220]

Jeon, Yoo chan,

[308]

Freeman, David Wayne, [414]

Hanagandi, Vijaykumar, [361]

Jiang, Jianhua,

[205]

Fr¨ ohlich, J¨ urg,

[393]

Hancock, Peter J. B.,

Jiang, Minga,

[519]

¨ Fuat Uler, G¨ ok¸ce,

[364]

Hansen, Kim Kortermand,

Jin, Albert Yongwon,

[411]

Fujiki, Cory,

[136]

Harik, Georges Raif,

[404]

Johansson, Christian,

[24]

Furtado, Jo˜ ao Carlos,

[418]

Harju, P. Taneli,

[398]

Johnson, Mika,

[441]

Galarce, Carlos E.,

[138]

Hart, William Eugene,

[305]

Jones, A.,

[112]

Gandham, Ravi V.,

[139]

Hartmann, D.,

[486]

Jones, Martin Harrison, [351]

Gantzlin, J.,

[140]

Hartmann, Uwe,

[194]

Jones, Terry,

[370]

Gao, Xiao-Zhi,

[451]

Haverinen, Janne,

[275]

Jong, Kenneth A. De,

[488]

Gates, Jr., George H.,

[47]

Hegde, Shailesh U.,

[143]

Juill´ e, Hugues,

[438]

Gathercole, Chris,

[416]

Heikkil¨ a, Anna-Mari,

[430]

Kadaba, Nagesh,

[522]

[507] [50]

Authors

K¨ am¨ ar¨ ainen, Olli,

17

[109]

Kampen, Antoine H. C. van,

[395]

Laurikkala, Jorma,

[226, 96]

Mason, Andrew J.,

[455]

Lawo, M.,

[531]

Mathias, Keith E.,

[538] [162]

Kampfner, R. R.,

[523]

Lay, Ming-Yi,

[313]

Mayer, Matthias,

Kanatis, S.,

[149]

Lazio, T. Joseph W.,

[403]

Mazza, Cecilia Beatriz, [222]

Kane, Couro,

[362]

Lee, Baumin,

[463]

McInerney, John,

[515]

Kanev, Youli Andreev,

[422]

Lee, Bogju,

[372]

Meng, Qing-chun,

[539]

Karavas, Vassilios N.,

[266]

Lee, Jinkoo,

[514]

Merkle, Laurence D.,

[163]

Kargupta, Hillol,

[363]

Lee, Michael Anthony,

[314]

Meyer, Thomas Patrick, [571]

Karjalainen, Risto,

[309]

Lehtinen, Joonas,

[283]

Michaud, Steven R.,

[23]

Karr, Charles L.,

[524]

Lehtiniemi, Tuukka,

[39]

Mikkola, Topi,

[15]

Kaski, Tuomas,

[30]

Leitch, Donald Dewar,

[350]

Moghadampour, Ghodrat,

Kaukoranta, Timo,

[439]

Lestander, Torbj¨ orn,

[265]

Keith, Mathias E.,

[330]

Levine, David Mark,

[312]

Kelly, Michael A.,

[150]

Lewis, James Eugene,

[252]

Kent, Simon,

[445]

L’Heureux, Pierre-Jean, [260]

Khoogar, Ahmad R.,

[525]

Li, Yong,

[583]

Kilkki, Juha,

[235]

Lichtfuß, H. J.,

[157]

Kim, Chi Han,

[342]

Lin, Chyi-Yeu,

[479]

Mosley, Randall Matthew,

Kim, G. H.,

[327]

Lin, Fang-Sheng,

[31]

Mott, Gregory F.,

[164]

Kim, Jinwoo,

[332]

Lin, Jin-Ling,

[513]

M¨ uck, Alexander,

[165]

Kim, Kieun,

[256]

Lin, Shyh-Chang,

[402]

M¨ uller, K. D.,

[520]

Kim, Suk-Jun,

[192]

Lin, Wei,

[359]

Napierala, G.,

[166]

Kitti, Mitri,

[12]

Lin, Yingqiang,

[270]

Nazarian, Bamshad,

[243]

Kivij”arvi, Juha,

[277]

Liu, J.,

[148]

Nettleton, David John, [365]

Knickmeier, Frank,

[151]

Lohbeck, T. K.,

[158]

Ngo, J. Thomas,

Knight, Leslie R.,

[156]

Lohmann, Reinhard,

[533]

Nguyen, Van Ky Quan, [285]

Kobes, E.,

[152]

Lohrmann, Hartmut,

[52]

Nice, William F.,

[56]

Koehn, Philipp,

[51]

Louis, Sushil John,

[534]

Nicholson, Mark,

[424]

Lu, Wei,

[268]

Nickel, J.,

[167]

Kommu, Venkataramana,

[526]

[287, 85,

108]

Mohammadi, A.,

[339]

Moilanen, Atte,

[409]

Monsieurs, Patrick,

[540]

Moon, Byung-Ro,

[316]

Moores, Mark David,

[227]

Moriarty, David E.,

[391] [425]

[541]

Kontio, Juho,

[28]

Magdalena, Luis,

[315]

Nieminen, Kimmo,

[20]

Koskim¨ aki, Esa,

[103]

Magyar, G´ abor,

[208]

Niesse, John Arthur,

[417]

Krasnogor, Natalio,

[236]

Maini, Harpal Singh,

[336]

Nims, III, Joseph White, [352]

Kristinsson, Kristinn,

[153]

Mandava, Venkat R.,

[159]

Niskanen, Antti O.,

[19, 273]

Kuiper, Herman,

[119]

Mandischer, Martin,

[160]

Nissinen, Ari S.,

[57, 431]

Kuo, Sheng-Feng,

[356]

Manela, Mauro,

[536]

Nordin, Peter,

[408]

Kursawe, Frank,

[433, 154]

Manikas, Theodore W., [448]

Obalek, J.,

[317]

L¨ ahteenm¨ aki, Jussi,

[101]

Mansfield, R. A.,

[161]

Odetayo, Michael O.,

[542]

Laine, Tei,

[87]

Mantere, Timo,

[257, 84, 107]

Oei, C. K.,

[168] [34]

Lamont, Gary B.,

[23]

M¨ antykoski, Janne,

[54]

Ogirala, Mythili,

Lampinen, Jouni,

[95, 440]

Marcus, Emil,

[392]

Olsan, James B.,

[169]

Langdon, William B.,

[380]

Maresky, Jonathan,

[55]

Olsson, Bj¨ orn,

[453]

Martin, N.,

[537]

¨ Omer, Bernhard,

[13, 102]

Laszewski, Gregor von, [530]

18


Opaterny, Thilo,

[58]

Richards, Robert A.,

[354]

Self, Steven,

O’Reilly, Una-May,

[353]

Riedel, H. J.,

[557]

Semertzidis, Michael T., [321]

Ostrowski, Tomasz,

[369]

Riionheimo, Janne,

[27]

Sen, Sandip,

[178] [412]

[185]

Pai, S.,

[18]

Rinderle, J.,

[175]

Sendhoff, Bernhard,

Palko, Sakari,

[59, 376]

Riolo, Rick L.,

[558]

Seniw, D.,

[568]

Robinson, Gordon M.,

[346]

Sheng, Lizeng,

[278]

Palmer, Charles Campbell,

[331]

Parish, Donald A.,

[60]

Rodel, Boris,

[86]

Shimizu, H.,

[91]

Parker, Gary B.,

[137]

Rogers, Leah Lucille,

[527]

Shu, Lingyan,

[528]

Parviainen, Olli,

[17]

Rojas-Guzm´ an, Carlos, [355]

Shun, Tongying,

[447]

Ros, Johannes P.,

[516]

Shyu, Ming-Suen,

[72]

Rosca, Justinian P.,

[405]

Siegmund, Frederik,

[186]

Peck, III, Charles Clyde, [318]

Rosenberg, R. S.,

[559]

Pedroso, Jo˜ ao Pedro,

Rosin, C.,

[389]

Rosmaita, Brian J.,

[176]

Roston, Gerald Paul,

[320]

Patcher, Ruth,

[23]

Pawlowsky, Marc Andrew,

[171]

[381]

Pe˜ na-Reyes, Carlos Andr´ es, P´ erez, Ra´ ul,

[231]

[400]

Perry, Z. A.,

[544]

Roth, Gerhard,

[560]

Persson, Johanna,

[172]

Rudnaya, Svetlana,

[443]

Pettey, Chrisila Cheri Baxter,

[545]

Rudnick, William Michael,

Sittisathanchai, Sinchai, [322] Skogstad, St˚ ale Andreas, [38]

[561]

Pinebrook, W. E.,

[546]

Rudolph, G¨ unter,

[177]

Pi˜ non, III, Elfego,

[368]

Ryyn¨ anen, Matti,

[279]

Smith, Brandye M.,

[245]

Smith, Robert Elliot,

[550, 174]

Smith, Stephen F.,

[562]

Sparvero, Louis John,

[454]

Spears, William M.,

[427, 187, 188]

Sprave, Joachim,

[189]

Sputek, K.,

[190]

Starkweather, Timothy John, Plum, T. W.-S.,

[547]

Saarenmaa, Liisa,

[563]

Podg´ orski, Jakub,

[25]

Salama, Rameri,

[211]

Pollhammer, G.,

[173]

Salminen, Tomi,

[14]

Poranen, Timo,

[280]

Samir, Mahfoud W.,

[367]

Sandqvist, Sam,

[238, 11]

Stevens, J.,

[191]

Sthamer, H.-H.,

[378]

Summa, Christopher Mark, Poshyanonda, Pipatpong,

[319]

Potter, Mitchell A.,

[399]

Sannier, Adrian V., II,

[564]

Potty, Gopu R.,

[217]

Santos, Almir G.,

[179]

Powell, David J.,

[548]

Schaffer, J. David,

[565]

Scheel, A.,

[566]

Prather, Jonathan Charles,

[204]

Suotula, Janne,

[93]

Swaminathan, R.,

[63]

Syed, Omar,

[73]

[569]

[232]

Szustakowski, Joseph D., [272] Tackett, Walter Alden,

[337]

Tadikonda, Satish Kumar,

[572]

Pullan, W. J.,

[379]

Schick, Carolyn Patricia, [201]

Pyylampi, Tero,

[110]

Schinke, H.,

[180]

Qi, Xiaofeng,

[549]

Schmidhuber, J¨ urgen,

[181]

Rada, R.,

[552]

Schmitt, II, Lawrence John,

Tanskanen, P.,

[209]

Radcliffe, Nicholas J.,

[553]

Schneider, Peter,

[170]

Taylor, Jeffrey Sniffen,

[420]

Ragg, Thomas,

[215]

Sch¨ urmann, Klaus,

[182]

Taylor, Timothy John,

[446]

Ramesh, Binoj,

[244]

Schwefel, Hans-Paul,

[183, 567]

Thangiah, Sam Rabindranath,

Ramos, Vitorino,

[105]

Schwehm, Markus,

[401]

Thierens, Dirk,

[357]

Rankin, Richard Patrick, [554]

Scott, Stephen D.,

[61]

Thomas, James D.,

[254]

Rasheed, Khaled,

[423]

Sedykh, Aleksandr Y.,

[242]

Thonemann, Ulrich Wilhelm,

Ravichandran, B.,

[555]

Seehase, Gerrit-Imme,

[62]

Thuiller, Wilfried,

[267]

Rechenberg, Ingo,

[556]

Sekanina, Luc´ aˇs,

[241]

Tibuleac, Sorin,

[444]

Rela, Leo,

[29]

Sekharan, D. Ansa,

[184]

Tiilikainen, Jouni,

[292]

Talbi, El-Ghazali,

[573]

Tanese, Reiko,

[574]

Tanskanen, Jarno M. A., [214] [311]

[575]

[193]

Authors

19

Todd, Peter M.,

[543]

Voget, Stefan,

[371]

Williams, K. P.,

[421]

Tofferi, Tuomo,

[42]

Voigt, Hans-Michael,

[578]

Wong, Hermean,

[347]

Tommiska, Matti,

[284]

Volmer, Marcel,

[228]

Wong, Yuk Yin,

[271]

Tompkins, George H.,

[358]

Vrijenhoef, Nico,

[100]

Wright, Ted,

[325]

T¨ orm¨ anen, Pasi,

[99]

Vuori, Jarkko,

[419]

Wronski, Jacob,

[33]

Tossavainen, Teppo,

[240]

Wakefield, Gregory H.,

[234]

Wu, Yu,

[199]

Tracey, Nigel James,

[219]

Wallace, Scott T.,

[74]

Tu, James Zhen,

[576]

Walter, Thomas,

[65]

Turner, Alasdair,

[64]

Walters, David C.,

[124]

Wan, Frank Lup Ki,

[132]

Wang, Bing,

[388]

Wang, Hsiu-Chi,

[36]

Wang, Lori A.,

[155]

Wanrooij, E. van,

Tuson, Andrew Laurence,

[323]

Tuson, Andrew L.,

[75]

Ulder, N. L. J.,

[195]

Unverfehrt, M.-T.,

[196]

Valenzuela-Rend´ on, Manuel,

[577]

van den Broek, Wilhelmus H. A. M., [407]

Xiao, Yong Liang (Leon),

[338]

Xiong, Y.,

[582]

Xu, Dexiang,

[300]

Yang, Cheng-Hong,

[478]

Yao, Leehter,

[529]

Ye, Jiang,

[41]

[66]

Yeh, E.-C.,

[360]

Weiland, H. H.,

[505]

Yin, Xiaodong,

[326]

Weile, Daniel S.,

[76]

Ying, Y. M.,

[77]

Vartiainen, Juha J.,

[282]

Weinacht, Thomas C.,

[212]

Yunker, James Milton,

[585]

Vasara, Petri,

[449]

Weinberg, R.,

[580]

Yuret, Deniz,

[67]

Vasconcelos, J. A.,

[333]

Weinberger, E. D.,

[581]

Zhang, Wenfeng,

[289]

Vaskelainen, Vesa,

[35]

Weinbrenner, Thomas,

[98]

Zhou, Yejin,

[584]

Vatilo, Jussi,

[37]

Werner, James Cunha,

[436]

Zitzler, Eckart,

[452]

Vemuri, Ram Mohan,

[334]

Weusthof, Heinz-Hubert, [198]

Zydallis, Jesse B.,

[23, 251]

Viskari, Tuomas,

[16]

White, David W.,

[299]

Vogelsang, J¨ org,

[197]

Wijkman, Pierre A. I.,

[406]

total 576 articles by 560 different authors

20


4.7

Subject index

All subject keywords of the papers given by the editor of this bibliography are shown next.

recombination,

acoustics

[81, 427]

cache management, CAD,

[114]

[524, 144, 548, 512, 123, 534, 320, 423]

inversion problems, [217]

statistical analysis,

[347]

noise control,

[436]

symmetry,

[246]

conceptual design,

[345]

active noise control,

[436]

temporal logic,

[238]

rapid prototyping,

[252]

Walsh functions,

[168]

shape design,

actuators [31]

animation,

[541]

piezoelectric,

[278, 285]

antennas,

[76, 216, 39]

[464, 474]

application,

[524]

adaptation,

aerospace, [369]

manufacturing,

aerodynamics,

[38] [157, 546]

agents

evolving, GP,

[129]

artificial life,

agriculture irrigation,

[390]

irrigation planning, [356] AI,

[495, 459]

analysing ES metastrategies,

artificial life,

[433]

analysing GA,

[497, 470, 465, 460, 545, 461, 126, 570, 536, 304, 318, 357, 371, 395, 24, 287]

[231] [434]

analytical,

[425]

drug design,

[338]

[14]

macromolecule,

[396]

[365, 438]

physical,

[305]

plants,

[323]

process,

[355]

[564, 551,

assembly

structural,

joints,

[259]

planning,

[208]

[532, 541,

379, 387, 395, 417]

chemometrics,

[407]

chemometry astronomy,

[403]

atomic clusters,

[417]

autonomous agents,

[129]

infrared spectroscopy, NIR spectroscopy,

[228]

[265]

chromosome

bin packing

reparing,

[415]

3D,

[428]

circuit design,

[480]

rapid prototyping,

[252]

cladistics,

[409]

[298, 413]

classification,

bin-packing,

analysing GA

[425]

chemistry [584]

446, 233]

[438] [540]

chemical reactions,

art

artificial intelligence,

autonomous,

breast, [368]

applications

ADC sigma-delta,

calibration, cancer

adaptive filters neural networks,

[45, 354, 364,

383, 95, 255]

piezo,

[343, 367, 96,

400]

3D,

[306]

axiomatisation,

[238]

building blocks,

[251]

complexity,

[236]

UV,

[242]

convergence,

[347]

biology,

[500]

fitness landscapes,

[370]

cell,

[220]

[353]

entomology,

[207]

mutation,

[427, 264]

metabolism,

[372]

niche,

[367]

seeds,

[265]

noise,

[363]

parallelism,

[328]

Petri nets,

[238]

Boolean multiplexer problem,

population size,

[251]

building blocks,

genetic programming,

biochemistry,

[559]

plastic,

[407]

spectra,

[274]

classifier systems,

[496, 558, 577, 155, 550, 354, 375, 395]

classifiers,

[395]

CLSP,

[68]

cluster molecular, clustering,

biomass estimation,

[417] [484, 15, 277]

clusters [281]

[298]

atomic, [155]

coding, delta,

[417] [507] [538]

Subject index

21

real,

[146, 300, 79,

inverted pendulum, [350]

diagnosis

417]

coevolution, 453, 240]

comparison branch and bound,

[263]

conventional graph plotting, implementation,

[88]

[89]

in artificial intelligence, in control,

fault,

light,

[227]

motor,

[99, 42]

nonlinear,

[457]

PID,

[99]

diesel engines,

[95, 440]

process,

[361]

differential equations,

[98]

quantum systems,

[212]

differential evolution?,

[538]

reactive power,

[16]

diffraction elements

robot,

[408, 230, 290]

[389, 399,

[365]

[350]

shape,

[285]

soft computing,

[451]

in machine learning, [343]

structures,

[426]

in protein folding,

[411]

tracking,

[179]

in TSP,

[311, 359]

Nelder-Mead,

[492]

in economic dispatch, in forest management,

[84] [32]

[424]

[406]

fuzzy,

[297, 350]

random search,

[358]

PID,

[579]

[463, 356,

395, 409, 411, 280]

[491]

tabu search,

[463, 409]

uniform,

[171, 494]

Re-

[194, 240]

[285]

rendering,

[439]

[349] [53] [53]

[37]

dithering,

[110]

diversity,

[246]

DJM,

[271]

docking,

[392, 394]

drug design,

[305, 392, 394]

data compression,

[385]

diodiversity,

[267]

global warming,

[267]

economics, [204]

[84]

[190, 483]

life cycle assessment, [449]

[249]

data mining

optimization,

[100]

paper industry,

[449]

databases,

[11]

project planning,

[356]

medical,

[204]

technical analysis,

[254]

[528, 380]

trading,

[309, 254]

data structures,

economy [521]

[78]

[511, 153, 132, 539, 308, 57, 98, 436]

[360]

[256]

economic dispatch problem,

data analysis

engineering components,

concurrent engineering, [344] control,

[296]

databases

computer science operating systems,

distribution networks,

ecology [586]

crystallography

medical,

computational geometry, [199]

ray tracing,

M-209,

X-ray,

compression

computer graphics,

[174]

QSAR, cryptology

composites

codebook generation,

diploidy,

sequencing, 3 parent,

[336]

laminates,

[178]

DNA

knowledge-based,

complexity,

DIPGAL,

crossover

[85]

Very Fast Simulated Annealing, [492]

[276]

[116, 554]

statistical,

traditional method, [85]

[443]

distribution system planning,

platform,

simulated annealing,

[205]

digital image correlation,

controllers

convergence,

desgin,

design,

[585]

[585]

[308]

diffractive element

pattern search,

responce surface method,

dianostics mechanical,

control systems real-time,

[139, 504]

econometrics,

[266]

forestry,

[563]

Eigen’s model,

[581]

index selection,

[138]

electrical motors,

[101]

marketing,

[11]

electrodynamics

aircraft,

[63]

elevators,

[85]

CAD,

[33]

fuzzy,

[579, 315, 99]

shape,

[383]

design,

[151, 534, 423]

undulator, electromagnetics, design,

[279] [333, 76, 393] [269]

22


scattering,

[262]

electronics

engineering nano-,

[276]

enginering

filters digital,

[435]

FIR,

[300, 293]

IIR,

[529, 398, 18]

morphological,

[435]

predictive,

[214]

assembly,

[441]

CAD,

[144]

microwaves,

[269]

PCB assembly,

[441]

sensoring,

[346]

radionuclides,

[22]

VLSI,

[429]

environmental science,

[449]

bitwise expected value,

enzymes,

[396]

landscape,

enegineering aerospace,

[285]

power,

[172]

energy HVAC, engineering,

[339] [183, 180,

machine,

[95]

entomology lepidopterology,

[207]

environment

ligands,

[454]

ESO,

[209]

evolution,

[503, 207]

learning,

[543]

simulation,

[349, 406]

trees,

[409]

499, 548]

aerospace,

[525, 60, 318, 63, 325, 345, 74, 249, 263, 278]

CAD, chemical,

evolution strategies, 140, 475, 173, 167,

[514] [557, 164,

[157, 183, 196, 486, 175, 180, 567, 510, 509, 456, 535, 506, 531, 134, 113, 469, 557, 190, 566, 505, 170, 471, 502, 130, 127, 433]

323, 361, 430]

evolution strategies civil, communal, construction,

[158] [486, 531,

CAD,

[152]

classic,

[556]

image processing,

[533]

konvergence,

[165]

control,

mutation,

[264]

electrical,

optimization,

[520]

[366, 431, 250]

[175]

parallel,

[177, 348]

machine,

[440]

recombination,

[317]

theory,

[197]

transputers,

[182]

mechanical,

[157, 196, 509, 134, 152, 320, 342, 33, 289]

military,

[169]

municipal,

[527]

nuclear,

[504]

pipes,

[158]

vector optimization, [154] evolutionary strateigies, [429]

[124, 504, 59, 326, 352, 360, 364, 84, 376, 95, 440, 213, 264]

power supplies,

[325]

process,

[253]

recombination operator, floating point GA,

[489]

FMS,

[462]

[421, 29]

structural,

[486, 510, 518, 327, 348, 373, 426, 206, 209, 235, 263, 268, 278, 285] [344]

[81]

forensics anthrax,

[274]

dental images,

[34] [563]

management,

[32]

pine,

[265] [241, 284, 293]

[365]

fuzzy logic,

[350, 372]

fuzzy reasoning,

[231]

fuzzy systems,

[314]

FuzzyCoCo,

[231]

GADELO,

[492]

GADO,

[423]

game theory

[406]

EXODUS,

[176]

experimental design,

[409]

GANNet,

[299]

expert systems,

[96]

GAP,

[411]

medical,

[226]

GARP,

[267]

fault dianostics,

[355]

feature selection, FEM, sheet metal,

[12]

[286]

[400, 407]

GATES,

[407]

[346, 244, 278]

generations

[289]

FET design,

Stackelberg,

GIS,

[45, 76, 214,

216, 274, 39]

engineering design,

[240]

EVOSIM, power,

software,

fitness landscape,

2D inverse,

electronics,

radio,

[87]

fractals

[59, 101, 16,

37]

[370]

dynamic,

FPGA,

130, 479]

[473]

fitness function

forestry,

[483, 339,

356, 77]

fitness

[269]

5000,

[407]

genetic algorithms,

[230]

genetic drift,

[347]

Subject index

23

genetic programming,

[145, 112, 519, 185, 150, 313, 329, 337, 69, 353, 82, 380, 98, 405, 408, 436, 25]

agents,

[540]

distributed,

[225]

learning,

[416] [181]

simulated annealing, [193] GENROUTE,

[494]

geochemistry,

[22]

geology oil,

[243]

geophysics, gravimetry,

[330, 447] [115]

inversion problems, [217] graph coloring,

[493]

graphs,

[15]

DAG,

[162]

partitioning,

[530, 316, 336]

plot,

[88]

set covering,

[418]

topological invariants, groundwater,

[280]

[527]

hardware evolvable,

[546]

integer programming,

HYPERGEN,

[156]

inverse problems

image compression

genetic programming

Prolog,

hydrodynamics,

wavelet, image processing,

[498, 159, 120, 560, 388, 408, 105, 435]

hill-climbing,

[359] [139]

linear programming, [584, 261] local search, Marquardt, neural networks,

[305, 409]

L-systems,

[349]

[80]

LAN,

[564]

multi-spectral,

[249]

laser forming,

[91]

NMR images,

[572]

lasers

vector quantization, [439] wavelets, image registration,

[283] [34, 291]

imaging microwaves,

[274]

[485]

job shop,

[584]

macro cell,

[448]

standard cell,

[340, 448]

learning,

[523, 563]

LiDAR,

[281]

implementation,

[176, 46]

load balancing,

[564]

C++,

[82, 88]

load cells,

[346]

Common LISP,

[188]

load flow problem,

[326]

Cray Y-MP8/864,

[512]

load forecast,

[264]

FORTRAN,

[583]

local hill-climbing,

[583]

[575]

machine learning,

[148, 61, 89,

382, 284] [128, 156]

IBM SP1,

[312]

Java,

[271]

Josephson junction, [273] MATLAB,

[57]

MIMD,

[305]

Prolog,

[181]

PVM,

[54]

Smalltalk-80,

[584]

vehicle routing,

[15]

[340]

XROUTE,

[522]

industrial economics complexity, instruction scheduling,

[562, 565, 498, 564, 542, 517, 476, 490, 512, 516, 528, 576, 129, 310, 407, 438]

machine learning

Hypercube,

tabu search,

[524]

sheet metal forming, [91] layout design,

[420]

[61]

hydrocyclone,

Kolmogorov complexity, [236]

[274]

VHDL,

[387]

[226]

T-ray,

[431]

hydrocarbons,

knowledge based systems,

immunology,

neuralnetworks,

[172]

[452]

machine vision,

[187, 319,

hydro power,

knapsack,

[72]

[342]

322, 410, 28]

[301]

enchancement,

hardware,

heuristics,

job shop scheduling,

[48]

[345]

[340]

[246]

edge detection,

helicopters,

GRASP,

Ising spin glass,

[110]

[234]

[361]

[262]

dithering,

hearing aid,

clustering,

[365]

scattering,

[276]

GIDEON,

[316]

2D fractals,

correlation,

[241]

hybrid,

[283]

[20]

control,

[457]

fuzzy,

[400]

hierarchical,

[405]

reinforcement,

[290]

supervised,

[416]

machine vision remote sensing,

[281]

management decision support,

[356]

manufacture sheet metal,

[91]

manufacturing assembly,

[259]

[240]

electronics assembly, [441]

[467]

FMS,

[86]

24


forming,

[244]

parts feeder,

[31]

process planning,

[295]

scheduling,

[17, 103, 109,

optimisation

motion planning kinematic,

multi-objective,

[525]

optimization,

[567, 456, 470, 477, 170, 458, 524, 574, 542, 461, 489, 490, 576, 549, 573, 62, 67, 404]

motors high speed,

[101]

induction,

[376]

261]

simulation,

[358]

manufacturing control,

[476]

Markov chains,

[347]

matching,

[555]

measurement film thickness,

music,

retina, medicine, anthrax,

optimization combinatorial,

[410]

composition,

[247]

natural languages,

[147]

nesting,

[413]

constrained,

[437]

cutting problem,

[319]

global,

[522, 553, 466, 504, 507, 512, 527, 160, 561, 194, 582, 481, 172, 44, 50, 319, 329, 412, 422, 450, 215]

[292]

neural networks

[291]

architecture,

[117]

[492]

decision,

[391]

[286]

design,

[104]

cancer,

[392]

filters,

[369]

diagnosis,

[96]

learning,

[275]

diagnostics,

[231]

modular,

[211]

drug design,

[338, 411]

review,

[51]

epidemiology,

[375, 286]

sequential,

[66]

human genetics,

[343]

obstetrics,

[204]

topology,

[299]

ophthalmology,

[291]

weights,

[305]

pharmacy,

[242]

neural networks 7evolution,

psychitry,

[200]

neural networks 7learning,

radiotherapy,

[302]

niche,

sensing,

[234]

[541, 305,

381, 401]

neural networks,

[34]

[578, 513,

310, 312]

medical imaging dental,

[23, 253]

large problems,

[49]

lot-sizing,

[68]

multi-modal,

[125]

multiobjective,

[462, 64, 366,

373, 452]

multivariable,

[298]

nonlinear,

[515]

simulation models,

[585]

trajectory,

[368]

transport networks, [582] parallel,

[468]

parallel GA, structure,

[143, 178, 564, 166, 501, 545, 189, 141, 128, 515, 163, 186, 192, 472, 123, 493, 156, 47, 305, 312, 52, 54, 58, 65, 328, 332, 92, 396, 401, 100, 420, 252, 256, 271]

[119, 57, 73,

211, 264]

parallel GA

methods,

urology,

[96, 226]

niching,

virology,

[420]

nondestructive testing

[233]

communication,

[55]

computer network,

[526]

distributed,

[574]

[94]

[544] [367]

parallel GP,

[246]

[225]

parallel processing FEM,

[83]

memetic algorithm,

[236]

MESO,

[209]

nonstationary functions, [174]

messy GA,

[489, 163, 47]

nuclear magnetic resonance,

messyGA,

[251]

on (oma),

[131]

Parkinson’s disease,

[242]

metabolic modeling,

[372]

Onemax,

[370]

path planning,

[294]

MIMD,

[553]

operators

pattern recognition,

[512]

minimum spanning tree, [191] mobile communications

eddy current,

[388]

adaptive probabilities, optics,

parameter estimation,

[529, 57]

parents [341]

[75]

[227]

3,

[491]

features,

[270]

protein fold,

[532]

CDMA,

[214]

design,

[442, 443, 205]

permutations,

[176]

mobile robots?,

[80]

diffraction,

[202]

petrology,

[243]

filters,

[444]

physics,

[508]

modeling acoustics,

[27]

quantum computing, [223]

astro-,

[403]

Subject index

25

mobile,

[137, 320, 275]

structure alignment, [272]

modular,

[307]

structure motifs,

path eplanning,

[487]

path planning,

[123, 294, 445]

walking,

[315]

celestial mechanics, [368]

spectroscopy,

high energy,

[422]

material,

[296]

molecular,

[377]

particle,

[45, 414, 279]

x-ray,

[292]

physiology respirator, planets, planning,

structure prediction, [23, 23] psychiatry diagnosis,

[42]

QAP,

[583]

[403]

QCL,

[13]

[537]

QSAR

[188, 407]

[350]

route planning,

[127]

routing,

[476, 478]

quality,

[494, 311,

100, 106, 15]

[253]

quantum computing,

[169]

vehicle,

[222]

experimental design, [248]

post mortem dental identification,

mobile,

aircraft,

chromatography, [367]

robots

[200] [253]

population size 100,

[272]

pulp bleaching,

population diversity,

[237, 245]

[19, 282, 288]

Royal Road functions,

[298]

rule based systems,

[562, 558, 231]

medicine,

[200]

rules

super conducting,

[35]

Boolean functions,

[258]

implementation,

[273]

procedures,

[102, 13]

[34]

fuzzy,

power engineering protection relays,

safety

[107, 108]

problems [361]

radiotherapy, program generators,

[136]

Prolog,

[230, 32]

protein folding,

[411, 260]

recombination, heuristic, de novo,

[232]

lattice model,

[111, 210]

[142]

[460, 118, 317] [303]

recycling waste plastic, prediction,

structures,

satellites,

[473]

[74]

scheduling,

[455, 133, 472, 122, 481, 569, 325, 229] [192]

forestry,

[32]

job shop,

[301, 322]

[263]

JSS,

[386, 402]

[22, 249]

project,

[93]

reliability

secondary structure prediction,

[473]

large Boolean expressions,

1 machine, [407]

[532, 47, 397,

236]

[430] [188]

3SAT,

[302]

random number generators,

process design, SAT,

quantum teleportation, [223] MINLP,

[297]

[321]

remote sensing, proteins forest, (Met)-enkephalin,

[47]

design,

[232]

docking,

[420, 224]

drug design,

[392, 394]

enzymes,

[454]

folding,

[70]

homology,

[385]

[281]

local,

respirator control, review,

Met-enkephalin,

germination, selection,

[14]

[195]

[265] [465, 363]

protein structure prediction, [41]

adaptive,

[116]

quantum computing, [97]

Hereford Ranch,

[351]

review?,

[161]

risk management,

[483]

RNA,

[454]

homology modeling, [397] HP-model,

[482, 552]

seeds

[42] [131]

artificial life,

search,

[210] [70]

robotics,

[525, 123,

NMR,

[341, 450]

QSAR,

[222]

learning,

[30]

signal,

[220]

machine learning,

[290]

329, 350]

sensing hearing,

[234]

sensor calibration,

[384]

sensor fusion,

[384]

sensors force, set covering problem,

[346] [71]

26


set partitioning,

[312]

shape design,

[333, 374,

Fourier,

[245]

UV,

imaging,

[249]

time series,

infrared,

[228, 237, 245]

neutron,

[414]

NIR,

[407, 265]

NMR,

[341, 450]

TimGA,

[88]

[201]

tolerances,

[514]

[274]

traffic signal,

[90]

[242] [57, 66]

423, 440]

aerodynamics, sheet forming,

[529, 388,

408, 419, 18]

acoustics,

[27]

photo electron,

ADC,

[38]

T-ray,

DSP,

[429]

wavelength selection,

[43, 300, 398,

statistical inference,

[228] [438]

214, 293]

statistics medical,

timetabling,

neural networks,

[369]

speech,

[28] [250]

silviculture steel purlins

transportation problems, [100] [522, 568, 478, 473, 298, 311, 316, 336, 359, 89, 441, 452, 236]

TSP parallel,

[166]

[268]

vehicle,

SIMD Steiner trees,

[56]

TSProuting

[32]

cold-formed, FEM,

[93]

transportation networks, [582]

[266]

experimental design, [248] noise,

school,

TSP,

[69]

econometrics,

management,

[571]

[289]

signal processing,

filters,

prediction,

[157, 183]

[575]

[149]

uniform crossover

[83]

structures simulated annealing, 493, 429]

simulater oil well,

[243]

simulation,

[580, 500, 547, 506, 121, 481, 492, 332, 358]

physics,

modified,

[502, 570,

steel beam,

[235]

subpopulation,

[184]

subpopulations,

[503, 312]

supervised thesis,

[257]

system estimation,

[98]

[198]

system identification, quantum computing, [13] software cost estimation,

[150]

testing,

[378]

software engineering software testing, software testing,

[469, 135,

132, 308, 313] [31]

telecommunications,

[419]

[107, 218,

mobile,

[214]

network design,

[331]

software,

[419]

vehicle routing,

[15]

time window,

[106]

time windows,

[221]

speciation,

[544]

testing GA,

spectroscopy,

[377, 203]

therapy

[324]

design,

[316, 429, 448]

layout design,

[340]

multichip modules,

[334]

FPGA,

[452] [225]

[378, 239,

257, 26, 36, 40]

[108]

vector quantization,

VLSI design,

real world problems, [312]

219, 21, 239, 257]

statistical analysis,

[78]

VLSI

testing

[29]

UNIX,

version spaces,

Taguchi,

[171]

[488]

Walsh functions,

[470]

wave length,

[407]

wind energy,

[213]

Annual index

4.8

27

Annual index

The following table gives references to the contributions by the year of publishing.

1965,

1993,

[157, 183]

122, 147, 539, 573,

1967,

[464, 559]

1970,

[482, 140, 196, 580]

1971,

[511, 556]

1972,

[497, 500, 547]

1973,

[537]

1974,

[486, 175, 180]

1975,

[488, 567]

1976,

[510]

1978,

[475, 509]

1979,

[456, 535]

1980,

[470, 562]

1981,

[477, 506, 523, 531, 552]

1982,

[474, 134, 546, 173]

1983,

[113, 499]

1984,

[469, 544, 557, 565, 190]

1985,

[496, 498, 503, 176, 566]

1986,

[116, 485, 136, 505, 145, 520, 167, 170]

1987,

[458, 152, 159, 181, 578, 581, 198]

[11, 457, 459, 462, 463, 117, 480, 481, 123, 484, 129, 491, 492, 493, 131, 513, 148, 521, 150, 526, 156, 532, 158, 534, 541, 169, 172, 549, 554, 555, 560, 179, 184, 579, 199, 584, 585]

472, 494, 536, 569,

473, 142, 162, 572,

1994,

[294, 295, 43, 44, 296, 45, 297, 298, 299, 300, 46, 301, 302, 303, 47, 304, 48, 49, 50, 305, 306, 307, 308, 309, 51, 310, 311, 312, 52, 313, 314, 53, 315, 54, 55, 316, 56, 57, 317, 58, 59, 60, 318, 319, 320, 61, 62, 321, 322, 63, 64, 323, 324, 65, 66, 325, 326, 67, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338]

1995,

[339, 340, 341, 342, 343, 344, 345, 68, 69, 346, 70, 71, 347, 348, 349, 350, 351, 72, 352, 353, 73, 354, 355, 356, 74, 357, 358, 75, 359, 76, 77, 360, 361, 362, 363, 78, 364, 365, 366, 367, 368, 369, 370, 371, 404]

1996,

[79, 372, 80, 373, 374, 81, 82, 375, 83, 84, 85, 376, 86, 377, 378, 87, 379, 88, 380, 89, 381, 382, 383, 384]

1997,

[385, 386, 387, 388, 389, 390, 90, 391, 392, 91, 92, 393, 93, 94, 394, 395, 95, 396, 96, 397, 97, 398, 399, 400, 401, 402, 403, 98, 99, 100, 405, 406, 407, 101, 408]

1998,

[17, 20, 409, 410, 411, 102, 412, 413, 103, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 104, 424, 425, 426, 105, 427, 428, 429]

1999,

[207, 430, 431, 106, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 107, 108, 442, 109, 110, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 111]

2000,

[12, 13, 200, 201, 202, 203, 204, 205, 206, 208, 209, 210, 211, 212, 213, 214, 215, 14, 15, 16, 216, 217, 218, 219, 281]

2001,

[220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 18, 230]

1988,

[468, 471, 121, 143, 174, 558, 178, 564]

1989,

[465, 487, 125, 502, 524, 525, 153, 165,

2002,

[19, 231, 232, 233, 234, 234, 235, 21, 22, 236, 237, 23, 23, 238, 239, 240, 241]

2003,

[242, 243, 244, 245, 24, 246, 247, 248, 249, 250, 251, 252, 253, 25, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272]

166, 187, 574, 577]

1990,

[460, 120, 130, 135, 138, 501, 144, 522, 154, 155, 530, 161, 542, 545, 548, 553, 177, 182, 188, 189, 195]

1991,

[112, 114, 461, 466, 467, 118, 479, 124, 489, 126, 132, 139, 141, 146, 517, 533, 538, 164, 550, 568, 191, 570, 575]

2004,

1992, 128, 519, 551, 583,

[455, 115, 119, 476, 478, 483, 127, 133, 495, 137, 504, 507, 508, 512, 514, 515, 516, 149, 151, 527, 528, 529, 160, 163, 540, 168, 543, 561, 563, 185, 186, 192, 571, 193, 576, 194, 197, 586]

490, 518, 171, 582,

[273, 274, 275, 276, 26, 277, 27, 28, 29, 278, 279, 280, 30]

2005,

[31, 32, 282, 33, 283, 34, 284, 285, 35]

2006,

[36, 286, 37, 287, 38, 39]

2007,

[40, 41, 288, 289, 290]

2008,

[291, 292, 293, 42]

28


4.9

Geographical index

The following table gives references to the contributions by country.

• Australia: [80, 379, 90, 274, 285, 293]

• Singapore: [77]

• Austria: [134, 173, 82, 102, 13]

• South Africa: [586]

• Belgium: [540, 326, 357, 381, 246]

• South Korea: [192, 327]

• Brazil: [418, 436, 21]

• Spain: [315, 400, 225]

• Canada: [477, 153, 114, 132, 528, 171, 560, 295, 340, 353, 81, 411, 450, 237, 260, 41]

• Sweden: [131, 172, 406, 453, 24, 265, 290]

• China: [539, 31, 264, 271] • Colombia: [231] • Denmark: [50, 229] • Finland: [563, 11, 49, 309, 54, 57, 59, 84, 85, 376, 87, 88, 382, 93, 94, 95, 96, 97, 398, 99, 101, 17, 20, 409, 103, 419, 104, 428, 430, 431, 106, 435, 439, 440, 441, 107, 108, 109, 110, 449, 451, 111, 12, 208, 209, 214, 14, 15, 16, 221, 223, 226, 230, 19, 235, 22, 238, 240, 257, 258, 268, 273, 275, 277, 27, 28, 29, 279, 280, 30, 282, 283, 284, 35, 37, 287, 39, 288, 292, 42]

• Switzerland: [393, 452] • Taiwan: [72, 36] • The Czech Republic: [241] • The Netherlands: [195, 119, 147, 44, 66, 395, 407] • United Kingdom: [161, 542, 553, 112, 164, 455, 133, 149, 185, 158, 536, 56, 64, 323, 346, 350, 75, 365, 366, 374, 378, 380, 383, 92, 410, 416, 421, 424, 429, 445, 446, 218, 219, 233, 236]

• Russia: [121]

• United States: [464, 559, 482, 580, 511, 497, 500, 547, 537, 488, 470, 562, 506, 523, 552, 474, 546, 499, 544, 565, 496, 498, 503, 176, 116, 485, 136, 145, 458, 159, 581, 143, 174, 558, 178, 564, 465, 125, 524, 525, 187, 574, 577, 460, 120, 135, 138, 522, 155, 545, 548, 188, 461, 466, 467, 479, 124, 489, 139, 517, 538, 550, 568, 191, 570, 575, 476, 478, 483, 128, 495, 137, 504, 512, 514, 515, 516, 518, 519, 527, 529, 163, 168, 543, 551, 561, 571, 576, 582, 583, 457, 459, 462, 463, 473, 122, 480, 481, 484, 129, 491, 492, 493, 494, 513, 148, 521, 150, 526, 156, 534, 162, 541, 169, 549, 554, 555, 179, 184, 569, 572, 579, 199, 584, 585, 296, 297, 298, 299, 300, 301, 302, 303, 47, 304, 48, 305, 306, 307, 308, 310, 311, 312, 313, 314, 316, 60, 318, 319, 320, 61, 63, 324, 325, 67, 328, 330, 331, 332, 334, 336, 337, 338, 339, 341, 342, 343, 344, 345, 69, 70, 347, 351, 352, 73, 354, 355, 356, 74, 358, 359, 76, 360, 361, 363, 78, 364, 367, 368, 370, 404, 79, 372, 375, 83, 377, 89, 384, 385, 386, 387, 388, 389, 390, 391, 392, 91, 394, 396, 397, 399, 402, 403, 405, 414, 415, 417, 420, 422, 423, 425, 426, 427, 207, 432, 434, 438, 442, 443, 444, 447, 448, 454, 201, 202, 203, 204, 205, 206, 210, 211, 212, 216, 217, 281, 220, 222, 224, 227, 18, 232, 234, 23, 239, 242, 244, 245, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 259, 261, 262, 263, 266, 269, 270, 272, 276, 278, 32, 33, 34, 286, 289, 291]

• Saudi Arabia: [26]

• Unknown country: [200]

• France: [123, 573, 294, 329, 333, 413, 213, 267] • Germany: [157, 183, 140, 196, 556, 486, 175, 180, 567, 510, 475, 509, 456, 535, 531, 113, 469, 557, 190, 566, 505, 520, 167, 170, 152, 181, 578, 198, 468, 471, 502, 166, 130, 501, 144, 154, 530, 177, 182, 189, 118, 126, 141, 533, 127, 508, 151, 160, 186, 193, 194, 197, 472, 142, 532, 43, 46, 51, 52, 53, 317, 58, 62, 65, 335, 68, 348, 349, 371, 401, 98, 100, 408, 412, 433, 437, 215, 40] • Israel: [487, 55, 86] • Italy: [490, 117, 45] • Mexico: [373] • New Zealand: [146] • Norway: [243, 38] • Poland: [369, 25] • Portugal: [105]

Chapter 5

Permuted title index The words of the titles of the articles are shown in the next table arranged in alphabetical order. The most common words have been excluded. The key word is shown by a disk (•) in the title field with the exception that it is omitted when appearing as the first word of the title after shown keyword. The other abbreviation used to compress titles are shown in appendix A.

[290] [405]

[305] Ability Embodied Evol. of Learning • Abstraction Hierarchical Learning with Procedural • [482] Mechanisms

[284] [45]

Acceleration Appl. of Reprog. mability in Alg. • acceleratori Ottimizzazione di cavitá RF per • di particelle

acid Modeling of metabolic syst. using fuzzy logic and supervisory simplex GA (enzyme kinetics, Escherichia coli, glycolysis, tricarboxylic • cycle) [206] acoustic Piezoceramic actuator placement for • cntr. of panels [324] acquisition Opt. rate concept • using version spaces and GAs [338] actinomycin Computer-assisted drug design: GAs and structures of molecular clusters of aromatic hydrocarbons and • D-deoxyguanosine [278] actuator Finite element analysis and GA opt. design for the • placement on a large adaptive structure [206] – Piezoceramic • placement for acoustic cntr. of panels [285] – Piezoelectric • design opt. for shape cntr. of smart composite plate structures [426] actuators Computational methods for the opt. of the mapping of • and sensors in the cntr. of flexible structures [511] adaptation Artificial gen. • in computer cntr. syst. [314] – Automatic design and • of fuzzy syst. and GAs using soft computing techniques [503] – Computer simulation of gen. • Par. subcomponent interaction in a multilocus model [474] – Intelligent behavior as an • to the task environment [275] • Through Stochastic Evol. Neuron Migration Process [475] Adaptationsaufgaben ESn zur numerischen Lösung von • (Dr. rer. nat.) [75] Adapting opertor probabilities in GAs [159] adaption A technique for search space • with simulated annealing & GAs in image registration [562] adaptive A learning syst. based on gen. • alg. [174] – An investigation of diploid GAs for • search on nonstationary functions [281] – An • Computer Vision Technique for Estimating the Biomass and Density of Loblolly Pine Plantations using Digital Orthophotography and LiDAR Imagery [488] – Analysis of the Behaviour of a Class of Gen. • Syst. [485] – Experimentation with an • search strategy for solving a key-board design/configuring problem [278] – Finite element analysis and GA opt. design for the actuator placement on a large • structure [500] • behavior of simulated bacterial cells subjected to nutritional shifts [227] • cntr. of the propagation of ultrafast light through random and nonlinear media

[372]

• • • • – – – – – –

global opt. with local search search using simulated evol. [116] sel. methods for cntr. convergence in GAs [138] Syst. and the Search for Opt. Index Sel. [369] Nonlinear • filtering: The GA appr. [497] Non-linearities in gen. • search [164] Optimising flowshop sch. through • GAs [390] Opt. of seasonal irrigation sch. by GAs • penalty) [256] Par. hierarchical • GA for genome sequencing [464] The behavior of • syst. which employ gen. and correlation alg. [543] – The evol. of learning: Simulating the interaction of • processes [304] – Thedetermination of invariant parameters and operators of the traditional GA using an • gen. alg. generator [62] adaptives Ein • Syst. zur Opt. von NFS [389] Adversaries Coevol. Search among • [222] affinities Quantitative-structure based predictions of displacer and protein • in chromatographic syst. [540] Agents Evolving Virtual • using Gen. Prog. [418] agrupamentos Algoritmo genético construtivo na otimiza¸ c˜ ao de problemas combinatoriais de • [234] Aid Hearing • Fitting with GAs [93] aikataulutuksessa A Study on the Use of GAs in Project Time Sheduling [Tutkimus geneettisten algoritmien kytst projektin • [63] aircraft Cntr. partitioning opt. for STOVL • using gen. search methods [524] air-injected Analysis and opt. of an • hydrocyclone [535] algebraischen Untersuchungen u ¨ ber die m¨ oglichkeit der automatischen entwicklung von • Formeln aus Daten mit hilfe der ES [402] Algorithm-Based Gen. • Sch. Syst. for Dynamic Job-Shop Scheduling Problems [530] Algorithmus Ein par. genetischer • f¨ ur das GraphPartitionierungsproblem [58] – Ein verteilt par. er genetischer • [508] – Ein wissensbasierter genetischer • zur Rekonstruktion physicalischer Ereignisse [107] algoritmeilla Automaattinen ohjelmien testaus optimoimalla geneettisill¨ a • [Automatic software testing by opt. with GAs] [95] algoritmilla Diesel-moottorin nokka-akselin muodon optimointi geneettisell¨ a • [Diesel engine cam shape design by GA] [39] – GA opt. of antennas for mobile terminals [Matkapuhelinantennien optimointi geneettisell¨ a• [110] – Rasterointimenetelmän kehittäminen mustesuihkutulostimelle geneettisell¨ a•

29

30

– VALMA-annoslaskentamallin rajoitettu optimointi geneettisell¨ a • [Constrained Opt. of the VALMA Dose Assessment Model by a GA] [42] algoritmin Geneettisen • soveltaminen moottoroidun hengityksensuojaimen toimintaparametrien optimointiin [418] Algoritmo genético construtivo na otimiza¸cão de problemas combinatoriais de agrupamentos [436] – Prog. a¸cão Genética + • Genético = CONTROLE GENETICO [Gen. Prog. + GA = Genetic Cntr. ] [246, 272] alignment A protein structure • method and appl. to the discovery of recurrent protein structure motifs [146] alleles GAs, annealing, and dimension • [77] allocation Berth • planning using GAs [85] – Hissien ohjausjärjestelmien tilastollinen vertailu [A statistical comparison of two elevator call • method] [573] • de processus sur les architectures parall` eles a ´ m´ emoire distribu´ ee [140] Analogrechner Simulation einer unterschaligen Schwebewaage auf einem • und Opt. ihres einsschwingverhaltens mit der ES [38] analog-to-digital [optimising delta-signa • converter filtering parameters] [472] Analyse Flowshop Scheduling mit Par. en Genetischen Algorithmen – Eine problemorientierten • genetischer Suchstrategien [461] analysis A critical • of GAs for global opt. [89] – A Description, • and Comparison of a Hardware and Software Impl. of the SPLASH GA for opt. symmetric traveling salesman problems [545] – An • of a par. GA [513] – An • of GA behavior for comb. opt. problems [353] – An • of Gen. Prog. [465] – An • of the effects of sel. in GAs [251] – Explicit building-block multiobjective GAs: Theory, • and development [270] – Feature synthesis and • by evol. computation for object detection and recognition [516] – Learning Boolean functions with GAs: A PAC • [237] – Mid-infrared biospectroscopic • of biological syst. in vitro and in situ [549] • and Appl. of Darwinian opt. Alg. in the Multidimensional Spaces [357] • and Design of GA [443] • and opt. design of diffractive optical elements [524] • and opt. of an air-injected hydrocyclone [318] • of GAs from a global random search method perspective with techniques for Alg. improvement [488] • of the Behaviour of a Class of Gen. Adaptive Syst. [292] – Novel Gen. Fitting Alg. and Statistical Error • Method for X-ray Reflectivity • [31] – Optimum design of a piezo-feeder based on dynamic • [74] – Par. orbit propagation and the • of satellite constellations [347] – Perf. • for GAs [205] – Rigorous • and design of diffractive optical elements [203] – Spectroscopic modeling and • of plasma conditions in implosion cores [245] – The appl. of single-pass attenuated total reflectance Fourier transform infrared spectroscopy for protein • [399] – The Design and • of a Computational Model of Cooperative Coevol. [493] – The design, • and impl. of par. simulated annealing and parallel GAs for the composite graph coloring problem [577] – Two • tools to describe the operation of classifier syst. [108] – Using GAs in testing a distribution protection relay software — A statistical • [450] – Using numerical methods and artificial intelligence in NMR data processing and • [168] – Walsh function • of GAs of nonbinary strings [313] analyze Gen. prog. and its appl. to • dynamical syst. [541] Animation Global Opt. for Articulated Figures: Molecular Structure Prediction and Motion Synthesis for • [146] annealing GAs, • and dimension alleles [127] Ansatz Kombinierte Touren- und Standortplanung bei der Hausm¨ ullentsorgung mit einem evol. sstrategischen • [468] – Par. • zur Lösung des Quadratischen Zuordnungsproblems [216] antenna arrays Appl. of GAs to • [39] antennas GA opt. of • for mobile terminals [Matkapuhelinantennien optimointi geneettisell¨ a algoritmilla] [22]


Anthrax Evaluating the Spatial Ecology of • in North America: Examining Epidemiological Components Across Multiple Geographic Scales Using a GIS-Based Appr. [420] antibody-antigen Computational biology: Methods in automated molecular docking with appl. in industrial virology and • recognition [411] anticonvulsant Biologically driven molecular modeling for • drug design [175] Anwendbarkeit Untersuchung u ¨ ber die • der ES in der Nachrichtentechnik [315] aplicaci´ on Estudio de la coordinación inteligente en robots b´ıpedos: • de l´ ogica borrosa y algoritmos gen´ eticos [368] applicability An investigation of the • of GAs to spacecraft trajectory opt. [395] – The • of GAs to Complex Opt. Problems in Chemistry [246, 272] application A protein structure alignment method and • to the discovery of recurrent protein structure motifs [496] – A study of par. and prog. in classifier syst. and its • to classification in KL-ONE semantic networks [413] – Alg. Heuristiques et Evol. nistes: • à la Résolution du Probl´ eme de Placement de Formes Irr´ eguli` eres [124] – An • of GAs to the economic dispatch of power generation [549] – Analysis and • of Darwinian opt. Alg. in the Multidimensional Spaces [554] – Considerations for rapidly converging GAs designed for • to problems with expensive evaluation functions [225] – Distr. Gen. Prog. Models with • to Logic Synthesis on FPGAs [308] – GA based non-linear modeling and its • to cntr. and mechanical diagnostics [561] – GAs and fitness variance with an • to the automated design of artificial neural networks [539] – GAs and their • to problem resolution and to syst. cntr. [313] – Gen. prog. and its • to analyze dynamical syst. [326] – Investigation on the • of GAs to the Load Flow Problem in Electrical Power Syst. [457] – Machine learning with rule extraction by gen. assisted reinforcement REGAR: • to nonlinear cntr. [366] – Multiobjective GAs with • to Cntr. Eng. Problems [70] • of hybridized GAs to the protein folding problem [422] • of neural networks and GAs in high energy physics [145] • of the GA to automatic prog. generation [264] – Novel mutation operators and their • to regularization of artificial neural networks [50] – Observing, Understanding, and cntr. the Gen. Method on a Neural Network • [294] – The Ariadne’s clew alg. : A general planning technique, • to automatic path planning [149] – The directed Steiner tree problem: An • of GAs [245] – The • of single-pass attenuated total reflectance Fourier transform infrared spectroscopy for protein analysis [532] – The • of the GA to protein tertiary structure prediction [462] applications A multi-objective simulation opt. method using a GA with • in manufacturing [398] – Advances in Polynomial Predictive Filtering: Theory, Design, and • [420] – Computational biology: Methods in automated molecular docking with • in industrial virology and antibody-antigen recognition [232] – Computational methods and their • for de novo functional protein design and membrane protein solubilization [536] – Contributions to the Theory and • of GAs [452] – Evol. Alg. for Multiobjective Opt. : Methods and • [365] – Evol. Alg. in AI: A Comparative Study Through • [408] – Evol. Prog. Induction of Binary Machine Code and its • [76] – GA • in electromagnetics [132] – GAs, their • and models in nonlinear syst. ident. [425] • and limitations of GAs for the opt. of multivariate calibration techniques [385] • of bioinformatics, homology modeling and QSAR to drug design [216] • of GAs to antenna arrays [284] • of Reprog. mability in Alg. Acceleration [214] – Polynomial predictive filters: Impl. and • [307] – Theory and • of modular reconfigurable robotic syst. [410] applied A hybrid neuro-gen. pattern evol. syst. • to musical composition [286]

Permuted title index

– A multiobjective appr. • to the protein structure prediction problem [41] – A Review of AI techniques • to Protein Structure Prediction [136] – An evaluation of Holland’s gen. operators • to a prog. generator [476] – GA based machine learning • to the dynamic routing of discrete parts [481] – GAs and neural networks • to manufacturing sch. [487] – GAs for order dependent processes • to robot pathplanning [169] – GAs • to a mission routing problem [432] – GAs • to nonlinear and complex domains [98] – Gen. Prog. Techniques • to Measurement Data [379] – Global opt. • to molecular architecture [242] – Studies in • computational chemistry: META model of photochemical reactions under UV under nat. conditions and an MCASE appr. to the search of a cure for Parkinson’s disease [88] Applying Geneettisten algoritmien soveltaminen suuntaamattomien verkkojen piirtoon • GAs to drawing undirected graphs] [73] Applying GAs to recurrent neural networks for learning network parameters and architecture [103] • Soft Computing in Manufacturing [Pehmolaskennan soveltaminen tehdasymp¨ arist¨ oss¨ a] [514] approximated Tolerance opt. using GA and • simulation [280] Approximation Alg. for Some Topological Invariants of Graphs [53] • der Rendering Equation durch Evol. are Alg. en [234] approximations Efficient model fitting using a GA: pole-zero • of HRTFs [400] Aprendizaje de reglas difusas usando algoritmos gen´ eticos [Concept Learning trought GAs] [301] architechture An • for job shop sch. with GAs [33] Architecture A Design Tool • for the Rapid Evaluation of Product Design Tradeoffs in an Internet-based Syst. Modeling Environment [73] – Applying GAs to recurrent neural networks for learning network parameters and • [379] – Global opt. appl. to molecular • [573] architectures Allocation de processus sur les • parall` eles ´ a m´ emoire distribu´ ee [44] – Local structure opt. in evol. generated neural network • [294] Ariadne’s clew The • alg. : A general planning technique, Appl. to automatic path planning [338] aromatic Computer-assisted drug design: GAs and structures of molecular clusters of • hydrocarbons and actinomycin D-deoxyguanosine [541] Articulated Global Opt. for • Figures: Molecular Structure Prediction and Motion Synthesis for Animation [41] Artificial A Review of • Intelligence techniques Appl. to Protein Structure Prediction [119] – Biological metaphors and the design of modular • neural networks [412] – Evol. of structures - Optimization of • neural structures for info processing [365] – Evol. Alg. in • Intelligence: A Comparative Study Through Appl. [495] – Evolving • Intelligence [446] – From • Evol. to Artificial Life [14] – Geneesys – katsaus kolmiulotteiseen keinoelämään nyt ja hahmotelma tulevaisuudesta [A Review of 3D • Life and Outline of its Future] [561] – GAs and fitness variance with an appl. to the automated design of • neural networks [117] – GAs for automatic design of • neural networks [233] – Innate Intelligence for • Organisms: via Species Evol. of Neural Networks [28] – Neuroevol. Based • Bandwidth Expansion of Telephone Band Speech [Neuroevoluutiopohjainen puhelinpuheen taajuuskaistan keinotekoinen laajentaminen] [511] • gen. adaptation in computer cntr. syst. [264] – Novel mutation operators and their appl. to regularization of • neural networks [185] – On the origin of effective procedures by means of • sel. [527] – Opt. groundwater remediation using • neural networks and the GA [551] – Studies in • evol. [23]

31

artificial intelligence Développement de méthodes bes´ ees sur les math´ ematiques, l’informatique et l’intelligence artificielle pour l’alignement de s´ equences et la pr´ ediction de structures prot´ eines [Development of mathematical, computing and • methods for the protein secondary structure prediction] [450] – Using numerical methods and • in NMR data processing and analysis [446] Artificial Life From Artificial Evol. to • [321] artificielle Développement de méthodes besées sur les math´ ematiques, l’informatique et l’intelligence • pour l’alignement de s´ equences et la pr´ ediction de structures prot´ eines [Development of mathematical, computing and artificial intelligence methods for the protein secondary structure prediction] [371] Aspekte genetischer Opt. salg. en: mathematische Modellierung und Einsatz in der Fahrplanerstellung [259] assembly Decomposition-based • synthesis of family of structures [441] – Operational and Tactical level Opt. in Printed Circuit Board • [449] assessment Environmental benchmarking: A framework for environmental • [22] – VALMA-annoslaskentamallin rajoitettu optimointi geneettisell¨ a algoritmilla [Constrained Opt. of the VALMA Dose • Model by a GA] [334] assignment GAs for partitioning, placement, and layer • for multichip modules [457] assisted Machine learning with rule extraction by gen. • reinforcement REGAR: Appl. to nonlinear cntr. [239] Assurance Computational Intelligence in Software Quality • [453] Asymmetric Alg. for Coevol. of Solutions and Fitness Cases in • Problem Domains [182] asynchroner Untersuchungen zur Effizienz mehrgliedriger • ESn auf Transputersyst. en [332] asynchronous Hierarchical, • par. GAs for simulationbased syst. design [417] atomic The structural opt. of • and molecular microclusters using a GA in real-valued space-fixed coordinates [469] ATP Kontinuierliche Regenerierung von • f¨ ur enzymatische Synthesen [245] attenuated The appl. of single-pass • total reflectance Fourier transform infrared spectroscopy for protein analysis [517] attribute-based Inductive learning of decision rules from • examples: A knowledge-intensive GA appr. [151] Auslegung eines Rechnernetzwerkes mit minimalem Kommunikationsaufwand mittels evol. ¨ arer Algorithmen [52] Auswertung Partielle • der Zielfunktion eines MPGA [107] Automaattinen ohjelmien testaus optimoimalla geneettisill¨ a algoritmeilla [Automatic software testing by opt. with GAs] [291] Automated A Novel • Appr. of Multi-Modality Retinal Image Registration and Fusion [219] – A Search-Based • Test-Data Generation Framework for Safety-Critical Software [310] – Alg. for comb. opt. in real-time and their • refinements by gen. -based learning [420] – Computational biology: Methods in • molecular docking with appl. in industrial virology and antibody-antigen recognition [561] – GAs and fitness variance with an appl. to the • design of artificial neural networks [360] • Electric Distribution Syst. Planning Using Intelligent Methods and Geographic Info System [235] • Formulation of Opt. models for Steel Beam Structures [572] • image segmentation and interpretation using GAs and semantic nets [345] – Using GAs as an • methodology for conceptual design of rotorcraft [36] automatic A hybrid GA for • test data generation [145] – Appl. of the GA to • prog. generation [107] Automatic Automaattinen ohjelmien testaus optimoimalla geneettisill¨ a algoritmeilla • software testing by opt. with GAs] [421] Automatic Evol. Alg. for • Par. ization [117] – GAs for • design of artificial neural networks [230] • and Evol. Robot Cntr. [314] • design and adaptation of fuzzy syst. and GAs using soft computing techniques [257] • Software Testing by GAs [321]

32

– The Ariadne’s clew alg. : A general planning technique, Appl. to • path planning [378] – The • Generation of Software Test Data using GAs [60] automating A GA appr. to • satellite range sch. [121] automation Evol. simulation method for • of radiophysics researches [531] Automatische Bemessung f¨ ur Stochastische Dynamische Belastung [535] automatischen Untersuchungen u ¨ ber die m¨ oglichkeit der • entwicklung von algebraischen Formeln aus Daten mit hilfe der ES [167] Automatisierung eines evol. sstrategischen Str¨ omungsexperiments [40] • von Strukturtests mit evol. ¨ aren Alg. en [129] autonomous agents Discovery learning in • using GAs [21] Avalia¸ c˜ aa Sele¸cão e • de Dados de Teste Baseadas em Prog. a¸ c˜ ao Gen´ etica [80] Avoidance Vision-based Obstacle • A Coevol. Appr. [500] bacterial Adaptive behavior of simulated • cells subjected to nutritional shifts [486] balkenartiger Opt. • Zylinderschalen aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical shells in reinforced concrete including elastic and plastic material behaviour] [28] Band Neuroevol. Based Artificial Bandwidth Expansion of Telephone • Speech [Neuroevoluutiopohjainen puhelinpuheen taajuuskaistan keinotekoinen laajentaminen] [28] Bandwidth Neuroevol. Based Artificial • Expansion of Telephone Band Speech [Neuroevoluutiopohjainen puhelinpuheen taajuuskaistan keinotekoinen laajentaminen] [21] Baseadas Sele¸cão e Avalia¸cãa de Dados de Teste • em Prog. a¸ c˜ ao Gen´ etica [392] basic Determination of 3D structure of suramin in solution and model of interaction of suramin with • fibroblast and platelet-derived growth factors [17] Batch Ennakoivaan simulointiin perustuva panostuotannon optimointi • production opt. by evol. computation and predictive simulation] [486] beamlike Opt. balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of • cylindrical shells in reinforced concrete including elastic and plastic material behaviour] [500] behavior Adaptive • of simulated bacterial cells subjected to nutritional shifts [513] – An analysis of GA • for comb. opt. problems [207] – Butterfly oviposition • pika biogeography, and lentiviral seuence evol. [474] – Intelligent • as an adaptation to the task environment [464] – The • of adaptive syst. which employ gen. and correlation alg. [488] Behaviour Analysis of the • of a Class of Gen. Adaptive Syst. [486] – Opt. balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical shells in reinforced concrete including elastic and plastic material • [531] Belastung Automatische Bemessung f¨ ur Stochastische Dynamische • [531] Bemessung Automatische • f¨ ur Stochastische Dynamische Belastung [449] benchmarking Environmental • A framework for environmental assessment [99] benefit Geneettisten algoritmien käyttö tutkittaessa sumean logiikan hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the • of fuzzy logic for PID-cntr. by means of GAs - case: frequency cntr. ] [77] Berth allocation planning using GAs [321] bes´ ees Développement de méthodes • sur les math´ ematiques, l’informatique et l’intelligence artificielle pour l’alignement de s´ equences et la pr´ ediction de structures prot´ eines [Development of mathematical, computing and artificial intelligence methods for the protein secondary structure prediction] [197] Betrachtungen Theoretische • zur Schrittweitensteuerung in ESn [252] bin packing Strategies of distr. GAs for threedimensional • in a SLS machine [428] Bin Packing Problem A GA for a Three-Dimensional Non-Convex • [294]


binarnych Zastosowanie operatorów ewolucyjnych do optymalizacji drzew • [408] Binary Evol. Prog. Induction of • Machine Code and its Appl. [489] • and floating-point function opt. using messy GAs [559] biochemical Simulation of gen. pop. with • properties [267] biodiversit´ e Impact des changements globaux sur la • en Europe : projections et incertitudes [207] biogeography Butterfly oviposition behavior, pika • and lentiviral seuence evol. [385] bioinformatics Appl. of • homology modeling and QSAR to drug design [119] Biological metaphors and the design of modular artificial neural networks [396] – Simulation of condensed-phase physical, chemical, and • syst. on massively par. computers (free energy perturbation, MIMD,malate dehydrogenase, enzymes, GA) [237] biological systems Mid-infrared biospectroscopic analysis of • in vitro and in situ [411] Biologically driven molecular modeling for anticonvulsant drug design [515] • Influenced Alg. and Par. in Nonlinear Opt. [556] biologischen ES: Opt. technischer Systeme nach Prinzipien der • Evolution [198] biologischer Simulation physikalischer und • Prozesse zur L¨ osung diskreter Opt. saufgaben [420] biology Computational • Methods in automated molecular docking with appl. in industrial virology and antibodyantigen recognition [281] Biomass An Adaptive Computer Vision Technique for Estimating the • and Density of Loblolly Pine Plantations using Digital Orthophotography and LiDAR Imagery [533] Bionische Verfahren zur Entwicklung visueller Systeme [237] biospectroscopic Mid-infrared • analysis of biological syst. in vitro and in situ [35] Bit Superconducting Tetrahedral Quantum • [253] bleaching Incorporation of environmental, economic and production quality criteria in multiobjective eng. design of chlorine/chlorine dioxide softwood kraft pulp • processes [546] body Drag minimization on a • of revol. [155] Boolean Classifier syst. learning of the • multiplexer function [516] – Learning • functions with GAs: A PAC analysis [258] Boolean Studies on • functions related to quantum computing [473] Boolean expressions GAs and the satisfiability of large-scale • [315] borrosa Estudio de la coordinación inteligente en robots b´ıpedos: aplicaci´ on de l´ ogica • y algoritmos gen´ eticos [404] bounded Learning gene linkage to effectively solve problems of • difficulty using GAs (problem solving, stochastic opt. ) [351] breeding The Hereford Ranch alg. : An improvement of GAs using selective • [483] bridge Risk-based • project sel. using GA opt. [217] Broadband nonlinear inversion for geoacoustic parameters in shallow water [190] budgetierungsmodellen Anwendung evolutorischer suchstrategien zur top-down-rechnung von • [251] building-block Explicit • multiobjective GAs: Theory, analysis, and development [207] Butterfly oviposition behavior, pika biogeography, and lentiviral seuence evol. [82] C++ Ein Kern f¨ ur genetisches Prog. mieren in C++ [Gen. prog. kernel in • [82] – Ein Kern f¨ ur genetisches Prog. mieren in • [Gen. prog. kernel in C++] [90] CabalBLmodel GA in dynamic traffic signal timing: the • [114] cache GAs and • replacement policy [255] CAD Functional requirements to shape generation in • [59] cage Structural opt. of • induction motors using finite element analysis [425] calibration Appl. and limitations of GAs for the opt. of multivariate • techniques [228] – Infrared spectroscopy in clinical chemistry, using chemometric • techniques [384] – Robust Sensor Fusion Alg. : • and Cost Minimization [95] cam Diesel-moottorin nokka-akselin muodon optimointi geneettisell¨ a algoritmilla [Diesel engine • shape design by GA] [440] • shape opt. by GA [25]


capacity A finite • sch. syst. for a silicon wafer manufacturer [Hienokuormitusjrjestelm piikiekkovalmistajalle] [453] Cases Alg. for Coevol. of Solutions and Fitness • in Asymmetric Problem Domains [45] cavit´ a Ottimizzazione di • RF per acceleratori di particelle [448] Cell A GA for Mixed Macro and Standard Cell Placement that Directly Incorporates • Membership Info [580] – Computer simulation of a living • [547] cell-assembly Simulation of a • model [500] cells Adaptive behavior of simulated bacterial • subjected to nutritional shifts [329] cellular Neural network synthesis using • encoding and the GA [492] cessation Relapse from tobacco smoking • Mathematical and computer micro-simulation modelling including parameter opt. with GAs [267] changements Impact des • globaux sur la biodiversité en Europe : projections et incertitudes [87] changing Using a GA for opt. in a • environment [78] Channels Study of Covert • in a Trusted Unix Syst. [571] chaotic Long-range predictability of high-dimensional • dynamics [279] Characterisation and opt. of hybrid insertion devices using GAs [276] Characterization New Metrological Techniques for Mechanical • at the Microscale and Nanoscale [361] chemical Process cntr. , opt. , and modeling of • syst. using GAs and neural networks [396] – Simulation of condensed-phase physical, • and biological syst. on massively par. computers (free energy perturbation, MIMD,malate dehydrogenase, enzymes, GA) [323] – The use of GAs to optimise • flowshops of unrestricted topology [355] chemical processes An EP appr. to probabilistic model-based fault diagnosis of • [434] chemical reaction Searching for • mechanisms with GAs [228] chemistry Infrared spectroscopy in clinical • using chemometric calibration techniques [242] – Studies in appl. computational • META model of photochemical reactions under UV under nat. conditions and an MCASE appr. to the search of a cure for Parkinson’s disease [395] – The Applicability of GAs to Complex Opt. Problems in • [228] chemometric Infrared spectroscopy in clinical chemistry, using • calibration techniques [407] Chemometrics in spectroscopic near infrared imaging for plastic material recognition [144] Chip-Assembly Strategien bei der Layout-Synthese nach Floorplan-Vorgaben [253] chlorine/chlorine Incorporation of environmental, economic and production quality criteria in multiobjective eng. design of • dioxide softwood kraft pulp bleaching processes [222] chromatographic Quantitative-structure based predictions of displacer and protein affinities in • syst. [415] chromosome A • repairing GA (CRGA) capable of finding exact solution [79] chromosomes New methods in gen. search with realvalued • [340] circuit Towards opt. • layout using advanced search techniques [273] circuits Cntr. of Quantum Evol. and Josephson Junction • [269] – Electromagnetic physical modeling of microwave devices and • [488] Class Analysis of the Behaviour of a • of Gen. Adaptive Syst. [537] – Convergence properties of a • of probabilistic schemes called reproductive plans [343] classification A comparison of GAs and other machine learning syst. on a complex • task from common disease research [496] – A study of par. and prog. in classifier syst. and its appl. to • in KL-ONE semantic networks [466] Classifier Cognitive Maps in Learning • Syst. [194] – Computational complexity of neural networks and • syst. [155] Classifier system learning of the Boolean multiplexer function [109]

33

[354]

Classifier System

Zeroth-Order Shape Opt. Utilizing

a Learning •

classifier systems A study of par. and prog. in • and its appl. to classification in KL-ONE semantic networks [550] – Default hierarchy formation and memory exploitation in learning • [558] – Empirical studies of default hierarchies and sequences of rules in learning • [577] – Two analysis tools to describe the operation of • [139] Climbing Evaluation of Hybrids of Hill • and GAs for Multiple Fault Diagnosis [228] clinical Infrared spectroscopy in • chemistry, using chemometric calibration techniques [484] clustering Monte Carlo validation of two gen. • alg. [277] – Opt. Methods for • [338] clusters Computer-assisted drug design: GAs and structures of molecular • of aromatic hydrocarbons and actinomycin D-deoxyguanosine [408] Code Evol. Prog. Induction of Binary Machine • and its Appl. [439] Codebook Iterative and Hierarchical Methods for • Generation in Vector Quantization [538] coding Delta • strategies for GAs [283] • of Wavelet-Transformed Images [507] • strategies for GAs and neural nets [453] Coevolution Alg. for • of Solutions and Fitness Cases in Asymmetric Problem Domains [399] – The Design and Analysis of a Computational Model of Cooperative • [231] Coevolutionary Fuzzy Modeling [389] • Search among Adversaries [80] – Vision-based Obstacle Avoidance: A • Appr. [105] Cognition Evol. and • in Image Analysis [466] Cognitive Maps in Learning CSs [212] coherent Using feedback for • cntr. of quantum syst. [268] cold-formed Optimum design of • steel purlins using GAs [372] coli Modeling of metabolic syst. using fuzzy logic and supervisory simplex GA (enzyme kinetics, Escherichia • glycolysis, tricarboxylic acid cycle) [72] color A GA appr. to • image enchancement [418] combinatoriais Algoritmo genético construtivo na otimiza¸ c˜ ao de problemas • de agrupamentos [208] Combinatorial On Solution Appr. for Some Industrially Motivated • Opt. Problems [310] combinatorial optimization Alg. for • in real-time and their automated refinements by gen. -based learning [513] – An analysis of GA behavior for • problems [51] Combining GAs and Neural Networks: The Encoding Problem [163] communication Generalizations and par. ization of messy GAs and • in parallel gen. alg. [55] – On effective • in distr. GAs [365] Comparative Evol. Alg. in AI: A • Study Through Appl. [585] – The opt. of simulation models by GAs: A • study [89] Comparison A Description, Analysis, and • of a Hardware and Software Impl. of the SPLASH GA for opt. symmetric traveling salesman problems [343] – A • of GAs and other machine learning syst. on a complex classification task from common disease research [85] – Hissien ohjausjärjestelmien tilastollinen vertailu [A statistical • of two elevator call allocation method] [84] – Sähkön hankinnan optimointi [Economic dispatch problem, a • of some solution methods] [343] complex A comparison of GAs and other machine learning syst. on a • classification task from common disease research [432] – GAs appl. to nonlinear and • domains [431] – Neural and Evol. Computing in Modeling of • Syst. [240] – Syst. Usability of • Tech. Syst. [395] – The Applicability of GAs to • Opt. Problems in Chemistry [194] complexity Computational • of neural networks and CSs [363] – Search, polynomial • and the fast messy GAs [460] – The time • of GAs and the theory of recombination operators [241] Component Appr. to Evolvable Syst. [480] • sel. opt. using GAs [496]

34

Components Evaluating the Spatial Ecology of Anthrax in North America: Examining Epidemiological • Across Multiple Geographic Scales Using a GIS-Based Appr. [285] composite Piezoelectric actuator design opt. for shape cntr. of smart • plate structures [493] – The design, analysis, and impl. of par. simulated annealing and parallel GAs for the • graph coloring problem [410] composition A hybrid neuro-gen. pattern evol. syst. appl. to musical • [377] compounds Data analysis strategies for qualitative and quantitative determination of organic compounds by Fourier transform infrared spectroscopy (signal processing, pattern recognition, GAs, volatile organic • [377] – Data analysis strategies for qualitative and quantitative determination of organic • by Fourier transform infrared spectroscopy (signal processing, pattern recognition, GAs, volatile organic compounds) [406] Computation Contributions to Evol. • [17] – Ennakoivaan simulointiin perustuva panostuotannon optimointi [Batch production opt. by evol. • and predictive simulation] [270] – Feature synthesis and analysis by evol. • for object detection and recognition [438] – Methods for Statistical Inference: Extending the Evol. • Paradigm [12] • of Incentive Stackelberg Solution [Stackelbergin pelin kannusteratkaisun laskeminen] [97] – On Quantum • [229] – Robust and Flexible Sch. with Evol. • [564] computational A • theory of learning in distr. syst. [311] – An empirical • study of GAs to solve order based problems: An emphasis on TSP and VRPTC [341] – An evaluation of the GA as a • tool in protein NMR [393] – Evol. Opt. for • Electromagnetics [534] – GAs as a • tool for design [263] – Issues of • efficiency in reliability-based structural opt. [420] • biology: Methods in automated molecular docking with appl. in industrial virology and antibody-antigen recognition [194] • complexity of neural networks and CSs [239] • Intelligence in Software Quality Assurance [232] • methods and their appl. for de novo functional protein design and membrane protein solubilization [426] • methods for the opt. of the mapping of actuators and sensors in the cntr. of flexible structures [523] • modeling of evol. learning [296] – Structure determination alg. in • X-ray crystallography [242] – Studies in appl. • chemistry: META model of photochemical reactions under UV under nat. conditions and an MCASE appr. to the search of a cure for Parkinson’s disease [399] – The Design and Analysis of a • Model of Cooperative Coevol. [512] computer-aided Neural network and gen. learning alg. for • design and pattern recognition [499] • gas pipeline operation using GAs and rule learning [152] Computer-Algorithmen Entwicklung von • zur Opt. von Strukturkomponenten nach der Evol. stheorie [338] Computer-assisted drug design: GAs and structures of molecular clusters of aromatic hydrocarbons and actinomycin D-deoxyguanosine [103] Computing Applying Soft • in Manufacturing [Pehmolaskennan soveltaminen tehdasymp¨ arist¨ oss¨ a] [321] – Développement de méthodes besées sur les math´ ematiques, l’informatique et l’intelligence artificielle pour l’alignement de s´ equences et la pr´ ediction de structures prot´ eines [Development of mathematical, • and artificial intelligence methods for the protein secondary structure prediction] [271] – DJM: Distr. Java Machine for Internet • [29] – Evol. • in search-based software eng. [19] – Holonomic quantum • [431] – Neural and Evol. • in Modeling of Complex Syst. [282] – Unitary Transformations for Quantum • [400] Concept Aprendizaje de reglas difusas usando algoritmos gen´ eticos • Learning trought GAs] [324] – Opt. rate • acquisition using version spaces and GAs [345] conceptual Using GAs as an automated methodology for • design of rotorcraft [286]


concrete Opt. balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical shells in reinforced • including elastic and plastic material behaviour] [344] concurrent engineering A constraint-based GA for • [396] condensed-phase Simulation of • physical, chemical, and biological syst. on massively par. computers (free energy perturbation, MIMD,malate dehydrogenase, enzymes, GA) [203] conditions Spectroscopic modeling and analysis of plasma • in implosion cores [242] – Studies in appl. computational chemistry: META model of photochemical reactions under UV under nat. • and an MCASE appr. to the search of a cure for Parkinson’s disease [262] conductors Two-dimensional time-domain inversion of perfect • using the GA [320] configuration A gen. methodology for • design [521] configurations Part sel. for predefined • using gen. search based alg. [560] consensus A • to primitive extraction [74] constellations Par. orbit propagation and the analysis of satellite • [526] constrained Enhanced GAs in • search spaces with emphasis in par. environments [437] – Evol. Alg. for • Opt. Problems [478] – Gen. search and time • routing [22] Constrained VALMA-annoslaskentamallin rajoitettu optimointi geneettisell¨ a algoritmilla • Opt. of the VALMA Dose Assessment Model by a GA] [344] constraint-based A • GA for concurrent eng. [337] construction Recombination, sel. , and the gen. • of computer prog. [418] construtivo Algoritmo genético • na otimiza¸cão de problemas combinatoriais de agrupamentos [352] Contingency ranking for voltage stability using a GA [423] Continuous GADO: A GA for • Design Opt. [584] – GA with qualitative knowledge enchancement for layout design under • space formulation [406] Contributions to Evol. Computation [536] • to the Theory and Appl. of GAs [227] control Adaptive • of the propagation of ultrafast light through random and nonlinear media [511] – Artificial gen. adaptation in computer • syst. [230] – Automatic and Evol. Robot • [426] – Computational methods for the opt. of the mapping of actuators and sensors in the • of flexible structures [288] – From the • of Quantum Syst. to Multiqubit Logic [308] – GA based non-linear modeling and its appl. to • and mechanical diagnostics [539] – GAs and their appl. to problem resolution and to syst. • [153] – GAs in syst. ident. and • [287] – GAs, Parameter • and Function Opt. : A New Appr. [579] – Intelligent • based on fuzzy alg. and GAs [457] – Machine learning with rule extraction by gen. assisted reinforcement REGAR: Appl. to nonlinear • [250] – Mixture-process experiments with • and noise variables [339] • and Operational methodologies for Energy-Efficient Operation of Building HVAC syst. [273] • of Quantum Evol. and Josephson Junction circuits [419] – Opt. of signal processing and network • in telecommunications syst. [206] – Piezoceramic actuator placement for acoustic • of panels [285] – Piezoelectric actuator design opt. for shape • of smart composite plate structures [436] Control] Prog. a¸cão Genética + Algoritmo Genético = CONTROLE GENETICO [Gen. Prog. + GA = Genetic • [451] Control Soft Computing Methods for • and Instrumentation [212] – Using feedback for coherent • of quantum syst. [366] Control Engineering Multiobjective GAs with Appl. to • Problems [424] Control System Selecting a Topology for SafetyCritical Real-Time • [436] CONTROLE Prog. a¸ c˜ ao Gen´ etica + Algoritmo Gen´ etico = • GENETICO [Gen. Prog. + GA = Genetic Cntr. ] [486]


controller Geneettisten algoritmien käyttö tutkittaessa sumean logiikan hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the benefit of fuzzy logic for PID-cntr. by means of GAs - case: frequency • [16] – Loistehon säätömodulin kehittäminen [Developing of the Reactive Power • [63] • partitioning opt. for STOVL aircraft using gen. search methods [297] controllers Gen. design of rule-based fuzzy • [116] controlling Adaptive sel. methods for • convergence in GAs [50] – Observing, Understanding, and • the Gen. Method on a Neural Network Appl. [116] convergence Adaptive sel. methods for cntr. • in GAs [537] • properties of a class of probabilistic schemes called reproductive plans [570] – Towards an extrapolation of the simulated annealing • theory onto the simple GA [554] converging Considerations for rapidly • GAs designed for appl. to problems with expensive evaluation functions [38] converter [optimising delta-signa analog-to-digital • filtering parameters] [399] Cooperative The Design and Analysis of a Computational Model of • Coevol. [315] coordinaci´ on Estudio de la • inteligente en robots b´ıpedos: aplicaci´ on de l´ ogica borrosa y algoritmos gen´ eticos [417] coordinates The structural opt. of atomic and molecular microclusters using a GA in real-valued space-fixed • [203] cores Spectroscopic modeling and analysis of plasma conditions in implosion • [248] correlated Response surface methods for experiments involving • noise variables [464] correlation The behavior of adaptive syst. which employ gen. and • alg. [81] – The Recombination Operator, its • to the Fitness Landscape and Search Perf. [150] cost A methodology for software • estimation using machine learning techniques [384] – Robust Sensor Fusion Alg. : Calibration and • Minimization [342] Coupler point path synthesis using a hybrid GA [78] Covert Study of • Channels in a Trusted Unix Syst. [415] CRGA A chromosome repairing GA • capable of finding exact solution [253] criteria Incorporation of environmental, economic and production quality • in multiobjective eng. design of chlorine/chlorine dioxide softwood kraft pulp bleaching processes [555] criterion Two-dimensional and three-dimensional model-based matching using a minimum Rep. • and a hybrid GA [491] crossover GAs with 3-parent • [171] – Modified Uniform • and Desegredation in GAs [586] cryptanalysis The use of GAs for • [296] crystallography Structure determination alg. in computational X-ray • [563] cultivation Induktiivinen oppiminen metsänviljelyn tietokannan tulkinnassa [Inductive learning in interpretation of databases of forest • [582] cumulative Opt. of transportation network design problems using a • GA and neural networks [242] cure Studies in appl. computational chemistry: META model of photochemical reactions under UV under nat. conditions and an MCASE appr. to the search of a • for Parkinson’s disease [388] current Signal processing and image restoration techniques for two-dimensional eddy • nondestructive evaluation [11] customers On finding opt. potential • from a large marketing database – A GA appr. [372] cycle Modeling of metabolic syst. using fuzzy logic and supervisory simplex GA (enzyme kinetics, Escherichia coli, glycolysis, tricarboxylic acid • [486] cylindrical Opt. balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike • shells in reinforced concrete including elastic and plastic material behaviour] [21] Dados Sele¸cão e Avalia¸cãa de • de Teste Baseadas em Prog. a¸ c˜ ao Gen´ etica [162] DAG Par. GA for the • vertex splitting problem [479] damped Gen. search methods for multicriterion opt. design of viscoelastically • structures [99]

35

Darwinian Analysis and Appl. of • opt. Alg. in the Multidimensional Spaces [11] database On finding opt. potential customers from a large marketing • – A GA appr. [563] databases Induktiivinen oppiminen metsänviljelyn tietokannan tulkinnassa [Inductive learning in interpretation of • of forest cultivation] [338] D-deoxyguanosine Computer-assisted drug design: GAs and structures of molecular clusters of aromatic hydrocarbons and actinomycin • [176] dealing Exodus: An extension of the GA to problems • with permutations [303] decision Heuristic recombination operators for multidimensional • problems [517] – Inductive learning of • rules from attribute-based examples: A knowledge-intensive GA appr. [391] – Symbiotic Evol. of Neural Networks in Sequential • Tasks [356] Decision support for irrigated project planning using a GA [261] decision-making Modeling and • in a semiconductor supply chain [259] Decomposition-based assembly synthesis of family of structures [558] default Empirical studies of • hierarchies and sequences of rules in learning classifier syst. [550] • hierarchy formation and memory exploitation in learning classifier syst. [396] dehydrogenase Simulation of condensed-phase physical, chemical, and biological syst. on massively par. computers (free energy perturbation, MIMD,malate • enzymes, GA) [538] Delta coding strategies for GAs [38] delta-signa [optimising • analog-to-digital converter filtering parameters] [30] demanding Taitoa vaativien tehtävien oppiminen ja suoritus WorkPartner-robotilla [Learning and performing skill • tasks with WorkPartner robot] [232] de novo Computational methods and their appl. for • functional protein design and membrane protein solubilization [281] Density An Adaptive Computer Vision Technique for Estimating the Biomass and • of Loblolly Pine Plantations using Digital Orthophotography and LiDAR Imagery [34] dental Multi reslution • image registration based on GAs [487] dependent GAs for order • processes appl. to robot path-planning [494] depot Genroute: A hybrid appr. for single and multiple • routing [171] Desegredation Modified Uniform Crossover and • in GAs [320] design A gen. methodology for configuration • [244] – A stabilized finite element formulation for the opt. • of forming processes [33] – A • Tool Architecture for the Rapid Evaluation of Product • Tradeoffs in an Internet-based Syst. Modeling Environment [398] – Advances in Polynomial Predictive Filtering: Theory, • and Appl. [331] – An appr. to a problem in network • using GAs [373] – An Empirical Study of Evol. Techniques for Multiobjective Opt. in Eng. • [443] – Analysis and opt. • of diffractive optical elements [357] – Analysis and • of GA [314] – Automatic • and adaptation of fuzzy syst. and GAs using soft computing techniques [119] – Biological metaphors and the • of modular artificial neural networks [411] – Biologically driven molecular modeling for anticonvulsant drug • [232] – Computational methods and their appl. for de novo functional protein • and membrane protein solubilization [95] – Diesel-moottorin nokka-akselin muodon optimointi geneettisell¨ a algoritmilla [Diesel engine cam shape • by GA] [104] – Evol. • of neural networks [278] – Finite element analysis and GA opt. • for the actuator placement on a large adaptive structure [423] – GADO: A GA for Continuous • Opt. [299] – GANNet: A GA for searching topology and weight spaces in neural network • The first step in finding neural network solution [383] – Generic Evol. • of Solid Objects using a GA [549]

36

– GA with qualitative knowledge enchancement for layout • under continuous space formulation [561] – GAs and fitness variance with an appl. to the automated • of artificial neural networks [534] – GAs as a computational tool for • [117] – GAs for automatic • of artificial neural networks [364] – GAs in the • opt. of electromagnetic devices [479] – Gen. search methods for multicriterion opt. • of viscoelastically damped structures [297] – Gen. • of rule-based fuzzy cntr. [332] – Hierarchical, asynchronous par. GAs for simulationbased syst. • [253] – Incorporation of environmental, economic and production quality criteria in multiobjective eng. • of chlorine/chlorine dioxide softwood kraft pulp bleaching processes [430] – Inherent Safety in Process Plant • - An Index-Based Appr. [548] – Inter-GEN: A hybrid appr. to eng. • opt. [512] – Neural network and gen. learning alg. for computeraided • and pattern recognition [202] • and opt. of optical diffractive elements using vector space projections and pseudo random encoding [289] • for uncertainties of sheet metal forming process [293] • of Digital Filters Using GAs [582] – Opt. of transportation network • problems using a cumulative GA and neural networks [31] – Optimum • of a piezo-feeder based on dynamic analysis [268] – Optimum • of cold-formed steel purlins using GAs [285] – Piezoelectric actuator • opt. for shape cntr. of smart composite plate structures [205] – Rigorous analysis and • of diffractive optical elements [236] – Studies on the Theory and • Space of Memetic Alg. [493] – The • analysis, and impl. of par. simulated annealing and parallel GAs for the composite graph coloring problem [399] – The • and Analysis of a Computational Model of Cooperative Coevol. [394] – The • of a ligand discovery and opt. syst. for structurebased drug design [463] – Three new alg. for exact D-opt. • problems [518] – Topological structural • using GAs [345] – Using GAs as an automated methodology for conceptual • of rotorcraft [485] design/configuring Experimentation with an adaptive search strategy for solving a key-board • problem [554] designed Considerations for rapidly converging GAs • for appl. to problems with expensive evaluation functions [204] detect Exploratory data analysis to • preterm risk factors [270] detection Feature synthesis and analysis by evol. computation for object • and recognition [498] detectors Machine learning procedures for generating image domain feature • [377] determination Data analysis strategies for qualitative and quantitative • of organic compounds by Fourier transform infrared spectroscopy (signal processing, pattern recognition, GAs, volatile organic compounds) [392] • of 3D structure of suramin in solution and model of interaction of suramin with basic fibroblast and platelet-derived growth factors [296] – Structure • alg. in computational X-ray crystallography [16] Developing Loistehon säätömodulin kehittäminen • of the Reactive Power Cntr. ] [20] Developing MILP-menetelmien kehittäminen • MILPmethods] [321] Development Développement de méthodes besées sur les math´ ematiques, l’informatique et l’intelligence artificielle pour l’alignement de s´ equences et la pr´ ediction de structures prot´ eines • of mathematical, computing and artificial intelligence methods for the protein secondary structure prediction] [46] development Eine Entwicklungsumgebung zum Monitoring Genetischer Algorithmen [A • tool for monitoring GAs] [251] – Explicit building-block multiobjective GAs: Theory, analysis, and • [137] – GAs for the • of real-time multi-heuristic search strategies [387] – Opt. hydrocarbon field • using a GA based appr. (reservoir) [397] – The • of new tools for homology modeling [279] devices Characterisation and opt. of hybrid insertion • using GAs [584]


– Electromagnetic physical modeling of microwave • and circuits [364] – GAs in the design opt. of electromagnetic • [139] Diagnosis Evaluation of Hybrids of Hill Climbing and GAs for Multiple Fault • [96] – Parameter Evaluation and Gen. -Based Rule Learning for the Differential • of Female Urinary Incontinence [200] Diagnostics A GA Method for Discovery of • Rules for Psychiatric Disorders [308] – GA based non-linear modeling and its appl. to cntr. and mechanical • [95] Diesel Diesel-moottorin nokka-akselin muodon optimointi geneettisell¨ a algoritmilla • engine cam shape design by GA] [95] Diesel-moottorin nokka-akselin muodon optimointi geneettisell¨ a algoritmilla [Diesel engine cam shape design by GA] [96] Differential Parameter Evaluation and Gen. -Based Rule Learning for the • Diagnosis of Female Urinary Incontinence [443] diffractive Analysis and opt. design of • optical elements [202] – Design and opt. of optical • elements using vector space projections and pseudo random encoding [205] – Rigorous analysis and design of • optical elements [180] Diffusors Opt. eines • nach der ES [400] difusas Aprendizaje de reglas • usando algoritmos gen´ eticos [Concept Learning trought GAs] [281] Digital An Adaptive Computer Vision Technique for Estimating the Biomass and Density of Loblolly Pine Plantations using • Orthophotography and LiDAR Imagery [293] – Design of • Filters Using GAs [300] – Opt. of FIR • filters using a real parameter par. GA and impl. s [435] digital filters Training based opt. of nonlinear • Case studies [43] digitaler Opt. • Filter mit genetischen Alg. en [146] dimension GAs, annealing, and • alleles [274] Dimensional Three • T-ray Inspection Syst. [134] dimensionierung Opt. e • technischer konstruktionen [253] dioxide Incorporation of environmental, economic and production quality criteria in multiobjective eng. design of chlorine/chlorine • softwood kraft pulp bleaching processes [178] Dipgal Distr. par. GAs • [174] diploid An investigation of • GAs for adaptive search on nonstationary functions [149] directed The • Steiner tree problem: An appl. of GAs [448] Directly A GA for Mixed Macro and Standard Cell Placement that • Incorporates Cell Membership Info [200] Discovery A GA Method for • of Diagnostics Rules for Psychiatric Disorders [246, 272] – A protein structure alignment method and appl. to the • of recurrent protein structure motifs [375] – Evol. -Assisted • of Sentinel Features in Epidemiologic Surveillance [226] – Knowledge • for Female Urinary Incontinence Expert Syst. [129] • learning in autonomous agents using GAs [394] – The design of a ligand • and opt. syst. for structurebased drug design [476] discrete GA based machine learning appl. to the dynamic routing of • parts [348] • opt. of structures under dynamic loading by using sequential and par. evol. strategies [358] – Opt. of quantitative variables in • event simulation models [343] disease A comparison of GAs and other machine learning syst. on a complex classification task from common • research [170] diskreten Alg. en zur Parameteradaption in der mehrgliedrigen ES bei der • Opt. [193] Diskreten Verbesserung des Simulated Annealing unter Anwendung Genetischer Programmierung am Beispiel des • Quadratischen Layoutproblems [198] diskreter Simulation physikalischer und biologischer Prozesse zur L¨ osung • Opt. saufgaben [200] Disorders A GA Method for Discovery of Diagnostics Rules for Psychiatric • [124] dispatch An appl. of GAs to the economic • of power generation [269]


displacer Quantitative-structure based predictions of • and protein affinities in chromatographic syst. [298] disruption Techniques for reducing the • of superior building blocks in GAs [64] Distinct GAs and Multiple • Solutions [573] distribu´ ee Allocation de processus sur les architectures parall` eles ´ a m´ emoire • [564] distributed A computational theory of learning in • syst. [220] – A dynamical model of the • interaction of intracellular signals [271] – DJM: • Java Machine for Internet computing [574] • GAs for function opt. s [225] • Gen. Prog. Models with Appl. to Logic Synthesis on FPGAs [178] • par. GAs Dipgal [55] – On effective communication in • GAs [156] – Hypergen – A • GA on a hypercube [252] – Strategies of • GAs for three-dimensional bin packing in a SLS machine [37] Distribution Multi-objective Reconfiguration of Medium Voltage • Networks [Keskij¨ anniteverkkojen kytkent¨ atilanteen monitavoitteinen jakorajaoptimointi] [108] – Using GAs in testing a • protection relay software — A statistical analysis [71] divide and conquer Evol. • for the set covering problem [271] DJM Distr. Java Machine for Internet computing [224] DNA repair protein Structural studies of the human • oxygen-6-alkylguanine-DNA alkyltransferase [498] domain Machine learning procedures for generating image • feature detectors [453] Domains Alg. for Coevol. of Solutions and Fitness Cases in Asymmetric Problem • [432] – GAs appl. to nonlinear and complex • [463] D-optimal Three new alg. for exact • design problems [22] Dose VALMA-annoslaskentamallin rajoitettu optimointi geneettisell¨ a algoritmilla [Constrained Opt. of the VALMA • Assessment Model by a GA] [475] Dr ESn zur numerischen Lösung von Adaptationsaufgaben • rer. nat.) [546] Drag minimization on a body of revol. [88] drawing Geneettisten algoritmien soveltaminen suuntaamattomien verkkojen piirtoon [Applying GAs to • undirected graphs] [411] driven Biologically • molecular modeling for anticonvulsant drug design [411] drug Biologically driven molecular modeling for anticonvulsant • design [385] drug design Appl. of bioinformatics, homology modeling and QSAR to • [338] – Computer-assisted • GAs and structures of molecular clusters of aromatic hydrocarbons and actinomycin Ddeoxyguanosine [394] – The design of a ligand discovery and opt. syst. for structure-based • [25] drzew Zastosowanie operatorów ewolucyjnych do optymalizacji • binarnych [429] DSP Evol. Strategies for the High-Level Synthesis of VLSI-Based • Syst. for Low Power [413] – Alg. Heuristiques et Evol. nistes: Appl. à la R´ esolution • Probl´ eme de Placement de Formes Irr´ eguli` eres [130] Durchbiegeminimierung Gewichts- und • von Fachwerktr¨ ager durch Anwendung der ES [348] dynamic Discrete opt. of structures under • loading by using sequential and par. evol. strategies [476] – GA based machine learning appl. to the • routing of discrete parts [90] – GA in • traffic signal timing: the CabalBLmodel [402] – GA-Based Sch. Syst. for • Job-Shop Scheduling Problems [122] • sch. of computer tasks using GAs [31] – Optimum design of a piezo-feeder based on • analysis [220] dynamical A • model of the distr. interaction of intracellular signals [313] dynamical systems Gen. prog. and its appl. to analyze • [571] dynamics Long-range predictability of highdimensional chaotic • [123] dynamique Alg. génétiques parallèles pour la planification de trajectoires de robots en environnement • [222]

37

[531]

Dynamische

Automatische Bemessung f¨ ur Stochastis-

che • Belastung

dynamischen Ein Evolutionsverfahren zur mathematischen Modellierung station¨ arer Zust¨ ande in • Systemen [192] Earliness Par. GAs for Single Machine Job Sch. with • and Tardiness Penalties [544] ecological Experimental study of speciation in • niche theory using GAs [286] Ecology Evaluating the Spatial • of Anthrax in North America: Examining Epidemiological Components Across Multiple Geographic Scales Using a GIS-Based Appr. [124] economic An appl. of GAs to the • dispatch of power generation [253] – Incorporation of environmental, • and production quality criteria in multiobjective eng. design of chlorine/chlorine dioxide softwood kraft pulp bleaching processes [84] Economic dispatch problem Sähkön hankinnan optimointi • a comparison of some solution methods] [388] eddy Signal processing and image restoration techniques for two-dimensional • current nondestructive evaluation [48] Edge etection using GAs [404] effectively Learning gene linkage to • solve problems of bounded difficulty using GAs (problem solving, stochastic opt. ) [143] Efficacy of par. GAs [263] efficiency Issues of computational • in reliability-based structural opt. [67] efficient From GAs to • opt. [234] • model fitting using a GA: pole-zero approximations of HRTFs [182] Effizienz Untersuchungen zur • mehrgliedriger asynchroner ESn auf Transputersyst. en [581] Eigen’s A stochastic generalization of • model of nat. sel. [186] Einfluß der Kommunikationstopologie auf massiv par. e Genetische Algorithmen [165] • verschiedener Wahrscheinlichkeitsverteilungen auf das Konvergenzverhalten von ESn [371] Einsatz Aspekte genetischer Opt. salg. en: mathematische Modellierung und • in der Fahrplanerstellung [509] Einsatz Der • eines Mikrorechners zur hybriden Opt. und Schwingungsanalyse [510] – FormOpt. von Leichtbaufachwerken durch • einer ESs [68] Einsatz Genetischer Algorithmen zur LosgrössenOpt. [557] • rechnergest¨ utzter Opt. mittels der ES zur l¨ osung galvanotechnischer Probleme [140] einsschwingverhaltens Simulation einer unterschaligen Schwebewaage auf einem Analogrechner und Opt. ihres • mit der ES [486] elastic Opt. balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical shells in reinforced concrete including • and plastic material behaviour] [486] elastischem Opt. balkenartiger Zylinderschalen aus Stahlbeton mit • und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical shells in reinforced concrete including elastic and plastic material behaviour] [360] Electric Distribution System Automated • Planning Using Intelligent Methods and Geographic Info Syst. [326] Electrical Power Systems Investigation on the Appl. of GAs to the Load Flow Problem in • [364] electromagnetic GAs in the design opt. of • devices [269] • physical modeling of microwave devices and circuits [393] Electromagnetics Evol. Opt. for Computational • [76] – GA appl. in • [443] elements Analysis and opt. design of diffractive optical • [202] – Design and opt. of optical diffractive • using vector space projections and pseudo random encoding [205] – Rigorous analysis and design of diffractive optical • [85] elevator Hissien ohjausjärjestelmien tilastollinen vertailu [A statistical comparison of two • call allocation method] [21] em Sele¸cão e Avalia¸cãa de Dados de Teste Baseadas • Prog. a¸ c˜ ao Gen´ etica [290] Embodied Evol. of Learning Ability [459] emergent Evol. alg. and • intelligence [311] emphasis An empirical computational study of GAs to solve order based problems: An • on TSP and VRPTC [526] – Enhanced GAs in constrained search spaces with • in par. environments [471]

38

empirical An • computational study of GAs to solve order based problems: An emphasis on TSP and VRPTC [373] – An • Study of Evol. Techniques for Multiobjective Opt. in Eng. Design [316] – Hybrid GAs with hyperplane synthesis: A theoretical and • study [558] • studies of default hierarchies and sequences of rules in learning classifier syst. [433] empirische Grundlegende • Untersuchungen der Parameter von ESn — Metastrategien [464] employ The behavior of adaptive syst. which • gen. and correlation alg. [72] enchancement A GA appr. to color image • [584] – GA with qualitative knowledge • for layout design under continuous space formulation [51] Encoding Combining GAs and Neural Networks: The • Problem [202] – Design and opt. of optical diffractive elements using vector space projections and pseudo random • [329] – Neural network synthesis using cellular • and the GA [396] energy Simulation of condensed-phase physical, chemical, and biological syst. on massively par. computers (free • perturbation, MIMD,malate dehydrogenase, enzymes, GA) [339] Energy-Efficient Cntr. and Operational methodologies for • Operation of Building HVAC syst. [95] engine Diesel-moottorin nokka-akselin muodon optimointi geneettisell¨ a algoritmilla [Diesel • cam shape design by GA] [373] Engineering An Empirical Study of Evol. Techniques for Multiobjective Opt. in • Design [29] – Evol. computing in search-based software • [253] – Incorporation of environmental, economic and production quality criteria in multiobjective • design of chlorine/chlorine dioxide softwood kraft pulp bleaching processes [548] – Inter-GEN: A hybrid appr. to • design opt. [526] Enhanced GAs in constrained search spaces with emphasis in par. environments [17] Ennakoivaan simulointiin perustuva panostuotannon optimointi [Batch production opt. by evol. computation and predictive simulation] [533] Entwicklung Bionische Verfahren zur • visueller Systeme [152] Entwicklung von Computer-Algorithmen zur Opt. von Strukturkomponenten nach der Evol. stheorie [535] – Untersuchungen u ¨ ber die m¨ oglichkeit der automatischen • von algebraischen Formeln aus Daten mit hilfe der ES [349] Entwicklungsprogrammen MathEvolvica – Simulierte Evol. von • der Natur [46] Entwicklungsumgebung Eine • zum Monitoring Genetischer Algorithmen [A development tool for monitoring GAs] [33] Environment A Design Tool Architecture for the Rapid Evaluation of Product Design Tradeoffs in an Internetbased Syst. Modeling • [474] – Intelligent behavior as an adaptation to the task • [87] – Using a GA for opt. in a changing • [449] environmental Environmental benchmarking: A framework for • assessment [253] – Incorporation of • economic and production quality criteria in multiobjective eng. design of chlorine/chlorine dioxide softwood kraft pulp bleaching processes [449] • benchmarking: A framework for environmental assessment [526] environments Enhanced GAs in constrained search spaces with emphasis in par. • [123] environnement Alg. génétiques parallèles pour la planification de trajectoires de robots en • dynamique [469] enzymatische Kontinuierliche Regenerierung von ATP f¨ ur • Synthesen [372] enzyme Modeling of metabolic syst. using fuzzy logic and supervisory simplex GA • kinetics, Escherichia coli, glycolysis, tricarboxylic acid cycle) [396] enzymes Simulation of condensed-phase physical, chemical, and biological syst. on massively par. computers (free energy perturbation, MIMD,malate dehydrogenase, • GA) [375] Epidemiologic Evol. -Assisted Discovery of Sentinel Features in • Surveillance [286] Epidemiological Evaluating the Spatial Ecology of Anthrax in North America: Examining • Components Across Multiple Geographic Scales Using a GIS-Based Appr. [311]


[18] [53]

Equalizers Global Opt. Techniques for IIR Phase • Equation Approximation der Rendering • durch Evol. are Alg. en

Ereignisse Ein wissensbasierter genetischer Algorithmus zur Rekonstruktion physicalischer • [292] Error Novel Gen. Fitting Alg. and Statistical • Analysis Method for X-ray Reflectivity Analysis [372] Escherichia Modeling of metabolic syst. using fuzzy logic and supervisory simplex GA (enzyme kinetics, • coli, glycolysis, tricarboxylic acid cycle) [99] Esimerkkin¨ a Geneettisten algoritmien käyttö tutkittaessa sumean logiikan hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - • taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the benefit of fuzzy logic for PID-cntr. by means of GAs - case: frequency cntr. ] [209] ESO The evol. structural opt. • method: Theoretical aspects and the modified evol. ary structural optimization (MESO) method [281] Estimating An Adaptive Computer Vision Technique for • the Biomass and Density of Loblolly Pine Plantations using Digital Orthophotography and LiDAR Imagery [150] estimation A methodology for software cost • using machine learning techniques [529] – Parameter • for nonlinear syst. [27] – Parameter • of a Plucked String Synthesis Model via the GA [260] Etude sur la generation de modeles de structures secondaires pour la prediction de structures proteiques [267] Europe Impact des changements globaux sur la biodiversit´ e en • : projections et incertitudes [565] evaluated Some experiments in machine learning using vector • GAs [99] Evaluating Geneettisten algoritmien käyttö tutkittaessa sumean logiikan hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at • the benefit of fuzzy logic for PID-cntr. by means of GAs - case: frequency cntr. ] [286] Evaluating the Spatial Ecology of Anthrax in North America: Examining Epidemiological Components Across Multiple Geographic Scales Using a GIS-Based Appr. [33] Evaluation A Design Tool Architecture for the Rapid • of Product Design Tradeoffs in an Internet-based Syst. Modeling Environment [136] – An • of Holland’s gen. operators appl. to a prog. generator [341] – An • of the GA as a computational tool in protein NMR [554] – Considerations for rapidly converging GAs designed for appl. to problems with expensive • functions [139] • of Hybrids of Hill Climbing and GAs for Multiple Fault Diagnosis [96] – Parameter • and Gen. -Based Rule Learning for the Differential Diagnosis of Female Urinary Incontinence [388] – Signal processing and image restoration techniques for two-dimensional eddy current nondestructive • [126] Evaluierung Parametrisierung und Konfigurierung genetischer Algorithmen [358] event Opt. of quantitative variables in discrete • simulation models [410] evolution A hybrid neuro-gen. pattern • syst. appl. to musical composition [350] – A New GA for the • of Fuzzy Syst. [482] – Adaptive search using simulated • [207] – Butterfly oviposition behavior, pika biogeography, and lentiviral seuence • [273] – Cntr. of Quantum • and Josephson Junction circuits [290] – Embodied • of Learning Ability [349] – MathEvolvica – Simulierte • von Entwicklungsprog. men der Natur [556] Evolution ES: Opt. technischer Systeme nach Prinzipien der biologischen • [446] Evolution From Artificial • to Artificial Life [233] – Innate Intelligence for Artificial Organisms: via Species • of Neural Networks [183] Evolution Kynernetische • als Strategie der experimellen Forschung in der Str¨ omungstechnik [105] Evolution and Cognition in Image Analysis [157] • eines Rohrkr¨ ummers [412] • of structures - Optimization of artificial neural structures for info processing [578] • und Opt. : Ein populationsgenetischer Zugang zu kombinatorischen Optimierungsproblemen [551] – Studies in artificial • [508]


[391]

–

Symbiotic • of Neural Networks in Sequential Decision

39

[115]

– –

Syst. Ident. through Simulated • The • of learning: Simulating the interaction of adaptive processes [40] evolution¨ aren Automatisierung von Strukturtests mit • Alg. en [151] evolution¨ arer Auslegung eines Rechnernetzwerkes mit minimalem Kommunikationsaufwand mittels • Algorithmen [348] evolution strategies Discrete opt. of structures under dynamic loading by using sequential and par. • [53] Evolutionare Approximation der Rendering Equation durch • Alg. en [275] Evolutionary Adaptation Through Stochastic • Neuron Migration Process [373] – An Empirical Study of • Techniques for Multiobjective Opt. in Eng. Design [355] – An • prog. appr. to probabilistic model-based fault diagnosis of chemical processes [230] – Automatic and • Robot Cntr. [523] – Computational modeling of • learning [406] – Contributions to • Computation [17] – Ennakoivaan simulointiin perustuva panostuotannon optimointi [Batch production opt. by • computation and predictive simulation] [270] – Feature synthesis and analysis by • computation for object detection and recognition [383] – Generic • Design of Solid Objects using a GA [44] – Local structure opt. in • generated neural network architectures [218] – Measuring • testability of real-time software [438] – Methods for Statistical Inference: Extending the • Computation Paradigm [431] – Neural and • Computing in Modeling of Complex Syst. [459] • alg. and emergent intelligence [370] • Alg. , Fitness Landscapes and Search [421] • Alg. for Automatic Par. ization [437] • Alg. for Constrained Opt. Problems [452] • Alg. for Multiobjective Opt. : Methods and Appl. [266] • alg. for statistics and finance [365] • Alg. in AI: A Comparative Study Through Appl. [335] • Alg. in Theory and Practice [445] • Appr. to Robot Path Planning [29] • computing in search-based software eng. [104] • design of neural networks [71] • divide and conquer for the set covering problem [393] • Opt. for Computational Electromagnetics [181] • principles in self-referential learning, or on learning how to learn: the meta-meta-...hook [408] • Prog. Induction of Binary Machine Code and its Appl. [121] • simulation method for automation of radiophysics researches [552] • structure and search [409] – Opt. with • alg. and local search [229] – Robust and Flexible Sch. with • Computation [427] – The Role of Mutation and Recombination • Alg. [209] – The • structural opt. (ESO) method: Theoretical aspects and the modified • structural optimization (MESO) method [429] Evolutionary Strategies for the High-Level Synthesis of VLSI-Based DSP Syst. for Low Power [375] Evolution-Assisted Discovery of Sentinel Features in Epidemiologic Surveillance [413] Evolutionnistes Alg. Heuristiques et • Appl. à la R´ esolution du Probl´ eme de Placement de Formes Irr´ eguli` eres [166] Evolutionsalgorithmus Ein par. er • zur Lösung des Travelling Salesman Problems [170] Evolutionsstrategie Alg. en zur Parameteradaption in der mehrgliedrigen • bei der diskreten Opt. [566] – Ein beitrag zur Theorie der • [557] – Einsatz rechnergest¨ utzter Opt. mittels der • zur l¨ osung galvanotechnischer Probleme [130] – Gewichts- und Durchbiegeminimierung von Fachwerktr¨ ager durch Anwendung der • [556] Evolutionsstrategie Opt. technischer Systeme nach Prinzipien der biologischen Evolution [567] Evolutionsstrategie und numerische Opt. [520] – Optimieren mit der • in der Industrie anhand von Beispielen [180] – Opt. eines Diffusors nach der • [135] [543]

Evolutionsstrategie

Opt.

gravimetrischer Modelle

mit der •

Tasks

Evolutionsstrategie Simulated annealing und • Ein vergleich anhand schweriger Opt. sprobleme [140] – Simulation einer unterschaligen Schwebewaage auf einem Analogrechner und Opt. ihres einsschwingverhaltens mit der • [175] – Untersuchung u ¨ ber die Anwendbarkeit der • in der Nachrichtentechnik [196] – Untersuchung zur Anwendung eines Verfahrens der • bei der Opt. von Leichtbaustrukturen [535] – Untersuchungen u ¨ ber die m¨ oglichkeit der automatischen entwicklung von algebraischen Formeln aus Daten mit hilfe der • [113] Evolutionsstrategien Das Konvergenzverhalten von • [165] – Einfluß verschiedener Wahrscheinlichkeitsverteilungen auf das Konvergenzverhalten von • [177] – Globale Opt. mit par. en • [433] Evolutionsstrategien Grundlegende empirische Untersuchungen der Parameter von • — Metastrategien [154] • f¨ ur die VektorOpt. [475] • zur numerischen L¨ osung von Adaptationsaufgaben (Dr. rer. nat.) [456] Evolutionsstrategien Optimieren mit • Reihenfolgeprobleme, nichtlineare und ganzzahlige Opt. [197] – Theoretische Betrachtungen zur Schrittweitensteuerung in • [182] – Untersuchungen zur Effizienz mehrgliedriger asynchroner • auf Transputersyst. en [317] Evolutionsstrategieren Rekombinationsoperatoren f¨ır • [510] Evolutionsstrategies FormOpt. von Leichtbaufachwerken durch Einsatz einer • [173] Evolutionsstrategische LastflußOpt. [167] evolutionsstrategischen Automatisierung eines • Str¨ omungsexperiments [127] – Kombinierte Touren- und Standortplanung bei der Hausm¨ ullentsorgung mit einem • Ansatz [505] – Opt. von Saugkopfeinläufen zur gewinnung mariner lockermaterialien mit hilfe der • Experimentiertechnik [152] Evolutionstheorie Entwicklung von ComputerAlgorithmen zur Opt. von Strukturkomponenten nach der • [471] Evolutionsverfahren Ein • zur mathematischen Modellierung station¨ arer Zust¨ ande in dynamischen Systemen [190] evolutorischer Anwendung • suchstrategien zur topdown-rechnung von budgetierungsmodellen [241] Evolvable Component Appr. to • Syst. [495] Evolving AI [247] • intelligent musical materials [66] • sequential neural networks for time series forecasting [540] • Virtual Agents using Gen. Prog. [211] – On • Modular Neural Networks [25] ewolucyjnych Zastosowanie operatorów • do optymalizacji drzew binarnych [128] examination An • of hypercube impl. s of GAs [286] Examining Evaluating the Spatial Ecology of Anthrax in North America: • Epidemiological Components Across Multiple Geographic Scales Using a GIS-Based Appr. [176] Exodus An extension of the GA to problems dealing with permutations [28] Expansion Neuroevol. Based Artificial Bandwidth • of Telephone Band Speech [Neuroevoluutiopohjainen puhelinpuheen taajuuskaistan keinotekoinen laajentaminen] [554] expensive Considerations for rapidly converging GAs designed for appl. to problems with • evaluation functions [183] experimellen Kynernetische Evolution als Strategie der • Forschung in der Str¨ omungstechnik [544] Experimental study of speciation in ecological niche theory using GAs [485] Experimentation with an adaptive search strategy for solving a key-board design/configuring problem [505] Experimentiertechnik Opt. von Saugkopfeinläufen zur gewinnung mariner lockermaterialien mit hilfe der evol. sstrategischen • [250] experiments Mixture-process • with cntr. and noise variables [248] – Response surface methods for • involving correlated noise variables [565] – Some • in machine learning using vector evaluated GAs [502]

40

Expert Systems Knowledge Discovery for Female Urinary Incontinence • [251] Explicit building-block multiobjective GAs: Theory, analysis, and development [328] Exploitable par. in GAs [550] exploitation Default hierarchy formation and memory • in learning classifier syst. [204] Exploratory data analysis to detect preterm risk factors [438] Extending Methods for Statistical Inference: • the Evol. Computation Paradigm [560] extraction A consensus to primitive • [457] – Machine learning with rule • by gen. assisted reinforcement REGAR: Appl. to nonlinear cntr. [570] extrapolation Towards an • of the simulated annealing convergence theory onto the simple GA [130] Fachwerktr¨ ager Gewichtsund Durchbiegeminimierung von • durch Anwendung der ES [392] factors Determination of 3D structure of suramin in solution and model of interaction of suramin with basic fibroblast and platelet-derived growth • [371] Fahrplanerstellung Aspekte genetischer Opt. salg. en: mathematische Modellierung und Einsatz in der • [259] family Decomposition-based assembly synthesis of • of structures [363] fast Search, polynomial complexity, and the • messy GAs [139] Fault Evaluation of Hybrids of Hill Climbing and GAs for Multiple • Diagnosis [355] fault diagnosis An EP appr. to probabilistic modelbased • of chemical processes [504] fault diagnostics Nuclear power plant • and thermal perf. studies using neural networks and GAs [184] feasible Manipulating subpop. of • and infeasible solutions in GAs [120] feature GAs for • sel. [498] – Machine learning procedures for generating image domain • detectors [270] Feature synthesis and analysis by evol. computation for object detection and recognition [375] Features Evol. -Assisted Discovery of Sentinel • in Epidemiologic Surveillance [212] feedback Using • for coherent cntr. of quantum syst. [57] feedforward Structural opt. of • neural networks using GA [83] FEM Mesh Mapping to a SIMD Machine Using GAs [226] Female Knowledge Discovery for • Urinary Incontinence Expert Syst. [96] – Parameter Evaluation and Gen. -Based Rule Learning for the Differential Diagnosis of • Urinary Incontinence [201] Femtosecond time-resolved photoelectron spectroscopy of phenol [392] fibroblast Determination of 3D structure of suramin in solution and model of interaction of suramin with basic • and platelet-derived growth factors [243] field Integrated • modeling [387] – Opt. hydrocarbon • development using a GA based appr. (reservoir) [541] Figures Global Opt. for Articulated • Molecular Structure Prediction and Motion Synthesis for Animation [43] Filter Opt. digitaler • mit genetischen Alg. en [398] Filtering Advances in Polynomial Predictive • Theory, Design, and Appl. [369] – Nonlinear adaptive • The GA appr. [38] – [optimising delta-signa analog-to-digital converter • parameters] [293] Filters Design of Digital • Using GAs [444] – Guided-mode resonance reflection and transmission • in the optical and microwave spectral ranges [300] – Opt. of FIR digital • using a real parameter par. GA and impl. s [214] – Polynomial predictive • Impl. and Appl. [266] finance Evol. alg. for statistics and • [309] financial markets Using GAs to find technical trading rules in • [109] finite A • capacity sch. syst. for a silicon wafer manufacturer [Hienokuormitusjrjestelm piikiekkovalmistajalle] [244] finite element A stabilized • formulation for the opt. design of forming processes [346] Finite Element Analysis GA Opt. of Load Cell Geometry by • [226]


Finite element analysis and GA opt. design for the actuator placement on a large adaptive structure [59] – Structural opt. of cage induction motors using • [376] finite element method Structural opt. of induction motor using GA and • [300] FIR Opt. of • digital filters using a real parameter par. GA and impl. s [453] Fitness Alg. for Coevol. of Solutions and • Cases in Asymmetric Problem Domains [370] – Evol. Alg. , • Landscapes and Search [561] – GAs and • variance with an appl. to the automated design of artificial neural networks [81] Fitness Landscape The Recombination Operator, its Correlation to the • and Search Perf. [234] fitting Efficient model • using a GA: pole-zero approximations of HRTFs [234] – Hearing Aid • with GAs [292] – Novel Gen. • Alg. and Statistical Error Analysis Method for X-ray Reflectivity Analysis [426] flexible Computational methods for the opt. of the mapping of actuators and sensors in the cntr. of • structures [229] – Robust and • Sch. with Evol. Computation [86] flexible manufacturing systems GAs for • [489] floating-point Binary and • function opt. using messy GAs [144] Floorplan-Vorgaben Chip-Assembly Strategien bei der Layout-Synthese nach • [472] Flowshop Scheduling mit Par. en Genetischen Algorithmen – Eine problemorientierten Analyse genetischer Suchstrategien [164] – Optimising • sch. through adaptive GAs [323] flowshops The use of GAs to optimise chemical • of unrestricted topology [66] forecasting Evolving sequential neural networks for time series • [447] – Interpretation, modeling and • runoff of regional hydrogeologic syst. [563] forest Induktiivinen oppiminen metsänviljelyn tietokannan tulkinnassa [Inductive learning in interpretation of databases of • cultivation] [32] – Searching for Prescriptive Treatment Schedules with a GA: A tool for • Management [238] formal Aspects of modelling and simulation of GAs: a • appr. [102] formalism A procedural • for quantum computing [550] formation Default hierarchy • and memory exploitation in learning classifier syst. [333] forme Opt. de • des structures électromagnétiques [535] Formeln Untersuchungen u ¨ ber die m¨ oglichkeit der automatischen entwicklung von algebraischen • aus Daten mit hilfe der ES [413] Formes Alg. Heuristiques et Evol. nistes: Appl. à la R´ esolution du Probl´ eme de Placement de • Irr´ eguli` eres [244] forming processes A stabilized finite element formulation for the opt. design of • [510] Formoptimierung von Leichtbaufachwerken durch Einsatz einer ESs [244] formulation A stabilized finite element • for the opt. design of forming processes [235] – Automated • of Opt. models for Steel Beam Structures [584] – GA with qualitative knowledge enchancement for layout design under continuous space • [183] Forschung Kynernetische Evolution als Strategie der experimellen • in der Str¨ omungstechnik [377] Fourier transform Data analysis strategies for qualitative and quantitative determination of organic compounds by • infrared spectroscopy (signal processing, pattern recognition, GAs, volatile organic compounds) [249] – Data compression alg. for the geosynchronous imaging • spectrometer [245] – The appl. of single-pass attenuated total reflectance • infrared spectroscopy for protein analysis [225] FPGAs Distr. Gen. Prog. Models with Appl. to Logic Synthesis on • [219] Framework A Search-Based Automated Test-Data Generation • for Safety-Critical Software [449] – Environmental benchmarking: A • for environmental assessment [278]


frequency Geneettisten algoritmien käyttö tutkittaessa sumean logiikan hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the benefit of fuzzy logic for PID-cntr. by means of GAs - case: • cntr. ] [519] function A hierarchical gen. syst. for symbolic • ident. [489] – Binary and floating-point • opt. using messy GAs [155] – Classifier syst. learning of the Boolean multiplexer • [574] – Distr. GAs for • opt. s [470] – GAs as • Opt. [477] – GAs for • opt. [125] – GAs in multimodal • opt. [287] – GAs, Parameter Cntr. and • Opt. : A New Appr. [232] functional Computational methods and their appl. for de novo • protein design and membrane protein solubilization [255] • requirements to shape generation in CAD [174] functions An investigation of diploid GAs for adaptive search on nonstationary • [554] – Considerations for rapidly converging GAs designed for appl. to problems with expensive evaluation • [516] – Learning Boolean • with GAs: A PAC analysis [258] – Studies on Boolean • related to quantum computing [291] Fusion A Novel Automated Appr. of Multi-Modality Retinal Image Registration and • [14] Future Geneesys – katsaus kolmiulotteiseen keinoel¨ am¨ a¨ an nyt ja hahmotelma tulevaisuudesta [A Review of 3D AL and Outline of its • [231] Fuzzy Coevol. • Modeling [297] – Gen. design of rule-based • cntr. [579] – Intelligent cntr. based on • alg. and GAs [99] fuzzy logic Geneettisten algoritmien käyttö tutkittaessa sumean logiikan hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the benefit of • for PID-cntr. by means of GAs - case: frequency cntr. ] [372] – Modeling of metabolic syst. using • and supervisory simplex GA (enzyme kinetics, Escherichia coli, glycolysis, tricarboxylic acid cycle) [350] Fuzzy Systems A New GA for the Evol. of • [314] fuzzy systems Automatic design and adaptation of • and GAs using soft computing techniques [423] GADO A GA for Continuous Design Opt. [557] galvanotechnischer Einsatz rechnergest¨ utzter Opt. mittels der ES zur l¨ osung • Probleme [299] GANNet A GA for searching topology and weight spaces in neural network design. The first step in finding neural network solution [456] ganzzahlige Optimieren mit ESn: Reihenfolgeprobleme, nichtlineare und • Opt. [499] gas Computer-aided • pipeline operation using GAs and rule learning [436] Gen´ etica Prog. a¸cão • + Algoritmo Genético = CONTROLE GENETICO [Gen. Prog. + GA = Genetic Cntr. ] [21] – Sele¸cão e Avalia¸cãa de Dados de Teste Baseadas em Prog. a¸ c˜ ao • [418] gen´ etico Algoritmo • construtivo na otimiza¸cão de problemas combinatoriais de agrupamentos [436] – Prog. a¸cão Genética + Algoritmo • = CONTROLE GENETICO [Gen. Prog. + GA = Genetic Cntr. ] [400] gen´ eticos Aprendizaje de reglas difusas usando algoritmos • [Concept Learning trought GAs] [315] – Estudio de la coordinación inteligente en robots b´ıpedos: aplicaci´ on de l´ ogica borrosa y algoritmos • [404] gene Learning • linkage to effectively solve problems of bounded difficulty using GAs (problem solving, stochastic opt. ) [14] Geneesys – katsaus kolmiulotteiseen keinoelämään nyt ja hahmotelma tulevaisuudesta [A Review of 3D AL and Outline of its Future] [95] geneettisell¨ a Diesel-moottorin nokka-akselin muodon optimointi • algoritmilla [Diesel engine cam shape design by GA] [39] – GA opt. of antennas for mobile terminals [Matkapuhelinantennien optimointi • algoritmilla] [110] – Rasterointimenetelmän kehittäminen mustesuihkutulostimelle • algoritmilla [22] – VALMA-annoslaskentamallin rajoitettu optimointi • algoritmilla [Constrained Opt. of the VALMA Dose Assessment Model by a GA] [42] Geneettisen algoritmin soveltaminen moottoroidun hengityksensuojaimen toimintaparametrien optimointiin [99]

41

geneettisill¨ a Automaattinen ohjelmien testaus optimoimalla • algoritmeilla [Automatic software testing by opt. with GAs] [93] geneettisten A Study on the Use of GAs in Project Time Sheduling [Tutkimus • algoritmien kytst projektin aikataulutuksessa] [99] • algoritmien k¨ aytt¨ o tutkittaessa sumean logiikan hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the benefit of fuzzy logic for PID-cntr. by means of GAs - case: frequency cntr. ] [88] • algoritmien soveltaminen suuntaamattomien verkkojen piirtoon [Applying GAs to drawing undirected graphs] [581] generalization A stochastic • of Eigen’s model of nat. sel. [163] Generalizations and par. ization of messy GAs and communication in parallel gen. alg. [44] generated Local structure opt. in evol. • neural network architectures [498] generating Machine learning procedures for • image domain feature detectors [36] generation A hybrid GA for automatic test data • [219] – A Search-Based Automated Test-Data • Framework for Safety-Critical Software [124] – An appl. of GAs to the economic dispatch of power • [145] – Appl. of the GA to automatic prog. • [260] – Etude sur la • de modeles de structures secondaires pour la prediction de structures proteiques [255] – Functional requirements to shape • in CAD [26] – GA based Test Data • [439] – Iterative and Hierarchical Methods for Codebook • in Vector Quantization [378] – The Automatic • of Software Test Data using GAs [136] generator An evaluation of Holland’s gen. operators appl. to a prog. • [304] – Thedetermination of invariant parameters and operators of the traditional GA using an adaptive gen. alg. • [383] Generic Evol. Design of Solid Objects using a GA [528] genetic-algorithm-based The impact of data structures on the perf. of • learning [96] Genetic-Based Parameter Evaluation and • Rule Learning for the Differential Diagnosis of Female Urinary Incontinence [322] Genetic-neuro scheduler [436] GENETICO Prog. a¸ c˜ ao Gen´ etica + Algoritmo Gen´ etico = CONTROLE • [Gen. Prog. + GA = Genetic Cntr. ] [310] genetics-based Alg. for comb. opt. in real-time and their automated refinements by • learning [82] genetisches Ein Kern f¨ ur • Prog. mieren in C++ [Gen. prog. kernel in C++] [256] genome Par. hierarchical adaptive GA for • sequencing [494] Genroute A hybrid appr. for single and multiple depot routing [217] geoacoustic Broadband nonlinear inversion for • parameters in shallow water [286] Geographic Evaluating the Spatial Ecology of Anthrax in North America: Examining Epidemiological Components Across Multiple • Scales Using a GIS-Based Appr. [360] Geographic Information System Automated Electric Distribution Syst. Planning Using Intelligent Methods and • [302] geometric Gen. and • opt. of three-dimensional radiation therapy treatment planning [442] geometrical GA opt. methods in • optics [346] Geometry GA Opt. of Load Cell • by Finite Element Analysis [249] geosynchronous Data compression alg. for the • imaging Fourier transform spectrometer [130] Gewichts und Durchbiegeminimierung von Fachwerktr¨ ager durch Anwendung der ES [505] gewinnung Opt. von Saugkopfeinläufen zur • mariner lockermaterialien mit hilfe der evol. sstrategischen Experimentiertechnik [575] Gideon A GA syst. for vehicle routing with time windows [286] GIS-Based Evaluating the Spatial Ecology of Anthrax in North America: Examining Epidemiological Components Across Multiple Geographic Scales Using a • Appr. [461] global A critical analysis of GAs for • opt. [305] – Adaptive • opt. with local search [107]

42

– Analysis of GAs from a • random search method perspective with techniques for Alg. improvement [379] • opt. appl. to molecular architecture [541] • Opt. for Articulated Figures: Molecular Structure Prediction and Motion Synthesis for Animation [18] • Opt. Techniques for IIR Phase Equalizers [401] Globale Opt. mit massiv par. en genetischen Algorithmen [177] • Opt. mit par. en ESn [267] globaux Impact des changements • sur la biodiversité en Europe : projections et incertitudes [372] glycolysis Modeling of metabolic syst. using fuzzy logic and supervisory simplex GA (enzyme kinetics, Escherichia coli, • tricarboxylic acid cycle) [493] graph coloring problem The design, analysis, and impl. of par. simulated annealing and parallel GAs for the composite • [530] Graph-Partitionierungsproblem Ein par. genetischer Algorithmus f¨ ur das • [280] Graphs Approximation Alg. for Some Topological Invariants of • [88] – Geneettisten algoritmien soveltaminen suuntaamattomien verkkojen piirtoon [Applying GAs to drawing undirected • [115] gravimetrischer Opt. • Modelle mit der ES [527] groundwater Opt. • remediation using artificial neural networks and the GA [392] growth Determination of 3D structure of suramin in solution and model of interaction of suramin with basic fibroblast and platelet-derived • factors [433] Grundlegende empirische Untersuchungen der Parameter von ESn — Metastrategien [444] Guided-mode resonance reflection and transmission filters in the optical and microwave spectral ranges [14] hahmotelma Geneesys – katsaus kolmiulotteiseen keinoel¨ am¨ a¨ an nyt ja • tulevaisuudesta [A Review of 3D AL and Outline of its Future] [84] hankinnan Sähkön • optimointi [Economic dispatch problem, a comparison of some solution methods] [89] Hardware A Description, Analysis, and Comparison of a • and Software Impl. of the SPLASH GA for opt. symmetric traveling salesman problems [148] – A general purpose • impl. of GAs [61] hardware-based HGA: A • GA [127] Hausm¨ ullentsorgung Kombinierte Touren- und Standortplanung bei der • mit einem evol. sstrategischen Ansatz [234] Hearing Aid Fitting with GAs [91] heat source A heating process alg. for metal forming by a moving • [91] heating A • process alg. for metal forming by a moving heat source [42] hengityksensuojaimen Geneettisen algoritmin soveltaminen moottoroidun • toimintaparametrien optimointiin [351] Hereford The • Ranch alg. : An improvement of GAs using selective breeding [583] Heuristic and exact alg. for the QAP [303] • recombination operators for multi-dimensional decision problems [187, 188] Heuristics Using Neural Networks and GAs as • for NP-Complete Problems [413] Heuristiques Alg. • et Evol. nistes: Appl. à la R´ esolution du Probl´ eme de Placement de Formes Irr´ eguli` eres [61] HGA A hardware-based GA [109] Hienokuormitusjrjestelm A finite capacity sch. syst. for a silicon wafer manufacturer • piikiekkovalmistajalle] [519] hierarchical A • gen. syst. for symbolic function ident. [439] – Iterative and • Methods for Codebook Generation in Vector Quantization [332] • asynchronous par. GAs for simulation-based syst. design [405] • Learning with Procedural Abstraction Mechanisms [256] – Par. • adaptive GA for genome sequencing [558] hierarchies Empirical studies of default • and sequences of rules in learning classifier syst. [550] hierarchy Default • formation and memory exploitation in learning classifier syst. [571] high-dimensional Long-range predictability of • chaotic dynamics [318]


High-Level Evol. Strategies for the • Synthesis of VLSI-Based DSP Syst. for Low Power [139] Hill Evaluation of Hybrids of • Climbing and GAs for Multiple Fault Diagnosis [458] hillclimbing Stochastic iterated gen. • [85] Hissien ohjausjärjestelmien tilastollinen vertailu [A statistical comparison of two elevator call allocation method] [136] Holland’s An evaluation of • gen. operators appl. to a prog. generator [19] Holonomic quantum computing [385] homology modeling Appl. of bioinformatics, • and QSAR to drug design [397] – The development of new tools for • [234] HRTFs Efficient model fitting using a GA: pole-zero approximations of • [224] human Structural studies of the • DNA repair protein oxygen-6-alkylguanine-DNA alkyltransferase [339] HVAC Cntr. and Operational methodologies for Energy-Efficient Operation of Building • syst. [99] hy¨ oty¨ a Geneettisten algoritmien käyttö tutkittaessa sumean logiikan • PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the benefit of fuzzy logic for PID-cntr. by means of GAs - case: frequency cntr. ] [36] hybrid A • GA for automatic test data generation [106] – A • GA for the vehicle routing problem with time windows [410] – A • neuro-gen. pattern evol. syst. appl. to musical composition [279] – Characterisation and opt. of • insertion devices using GAs [342] – Coupler point path synthesis using a • GA [359] – High quality tour • gen. schemes for TSP opt. problems [548] – Inter-GEN: A • appr. to eng. design opt. [316] • GAs with hyperplane synthesis: A theoretical and empirical study [494] – Genroute: A • appr. for single and multiple depot routing [555] – Two-dimensional and three-dimensional model-based matching using a minimum Rep. criterion and a • GA [509] hybriden Der Einsatz eines Mikrorechners zur • Opt. und Schwingungsanalyse [70] hybridized Appl. of • GAs to the protein folding problem [139] Hybrids Evaluation of • of Hill Climbing and GAs for Multiple Fault Diagnosis [172] hydro power GAs and neural networks for opt. of • production [387] hydrocarbon Opt. • field development using a GA based appr. (reservoir) [338] hydrocarbons Computer-assisted drug design: GAs and structures of molecular clusters of aromatic • and actinomycin D-deoxyguanosine [524] hydrocyclone Analysis and opt. of an air-injected • [447] hydrogeologic Interpretation, modeling and forecasting runoff of regional • syst. [128] hypercube An examination of • impl. s of GAs [156] – Hypergen – A distr. GA on a • [156] Hypergen – A distr. GA on a hypercube [316] hyperplane Hybrid GAs with • synthesis: A theoretical and empirical study [330] hyperspace Remapping • and subpartition sampling in iterative gen. search [519] identification A hierarchical gen. syst. for symbolic function • [153] – GAs in syst. • and cntr. [132] – GAs, their appl. and models in nonlinear syst. • [135] – Syst. • through Simulated Evol. [18] IIR Global Opt. Techniques for • Phase Equalizers [72] image A GA appr. to color • enchancement [291] – A Novel Automated Appr. of Multi-Modality Retinal • Registration and Fusion [572] – Automated • segmentation and interpretation using GAs and semantic nets [498] – Machine learning procedures for generating • domain feature detectors [34] – Multi reslution dental • registration based on GAs [388] – Signal processing and • restoration techniques for twodimensional eddy current nondestructive evaluation [105] Image Analysis Evol. and Cognition in • [429]


image registration A technique for search space adaption with simulated annealing & GAs in • [281] Imagery An Adaptive Computer Vision Technique for Estimating the Biomass and Density of Loblolly Pine Plantations using Digital Orthophotography and LiDAR • [283] Images Coding of Wavelet-Transformed • [407] imaging Chemometrics in spectroscopic near infrared • for plastic material recognition [249] – Data compression alg. for the geosynchronous • Fourier transform spectrometer [267] Impact des changements globaux sur la biodiversité en Europe : projections et incertitudes [528] – The • of data structures on the perf. of gen. -alg. -based learning [213] Implantation d’un système éolien, opt. par alg. g´ en´ etiques [89] Implementation A Description, Analysis, and Comparison of a Hardware and Software • of the SPLASH GA for opt. symmetric traveling salesman problems [148] – A general purpose hardware • of GAs [382] • and Alg. of a Tree Shape Par. Computer [54] – Par. • of GAs [214] – Polynomial predictive filters: • and Appl. [223] – Quantum Info Processing and its Linear Optical • [493] – The design, analysis, and • of par. simulated annealing and parallel GAs for the composite graph coloring problem [128] implementations An examination of hypercube • of GAs [300] – Opt. of FIR digital filters using a real parameter par. GA and • [203] implosion Spectroscopic modeling and analysis of plasma conditions in • cores [12] Incentive Computation of • Stackelberg Solution [Stackelbergin pelin kannusteratkaisun laskeminen] [267] incertitudes Impact des changements globaux sur la biodiversit´ e en Europe : projections et • [226] Incontinence Knowledge Discovery for Female Urinary • Expert Syst. [96] – Parameter Evaluation and Gen. -Based Rule Learning for the Differential Diagnosis of Female Urinary • [448] Incorporates A GA for Mixed Macro and Standard Cell Placement that Directly • Cell Membership Info [253] Incorporation of environmental, economic and production quality criteria in multiobjective eng. design of chlorine/chlorine dioxide softwood kraft pulp bleaching processes [336] • of knowledge in gen. recombination [430] Index-Based Inherent Safety in Process Plant Design - An • Appr. [408] Induction Evol. Prog. • of Binary Machine Code and its Appl. [59] – Structural opt. of cage • motors using finite element analysis [376] induction motor Structural opt. of • using GA and finite element method [563] Inductive Induktiivinen oppiminen metsänviljelyn tietokannan tulkinnassa • learning in interpretation of databases of forest cultivation] [517] Inductive learning of decision rules from attributebased examples: A knowledge-intensive GA appr. [563] Induktiivinen oppiminen metsänviljelyn tietokannan tulkinnassa [Inductive learning in interpretation of databases of forest cultivation] [420] industrial Computational biology: Methods in automated molecular docking with appl. in • virology and antibody-antigen recognition [208] Industrially On Solution Appr. for Some • Motivated Comb. Opt. Problems [520] Industrie Optimieren mit der ES in der • anhand von Beispielen [184] infeasible Manipulating subpop. of feasible and • solutions in GAs [438] Inference Methods for Statistical • Extending the Evol. Computation Paradigm [515] Influenced Biologically • Alg. and Par. in Nonlinear Opt. [448] Information A GA for Mixed Macro and Standard Cell Placement that Directly Incorporates Cell Membership • [412] – Evol. of structures - Optimization of artificial neural structures for • processing [223] – Quantum • Processing and its Linear Optical Impl. [159]

43

infrared Chemometrics in spectroscopic near • imaging for plastic material recognition [377] – Data analysis strategies for qualitative and quantitative determination of organic compounds by Fourier transform • spectroscopy (signal processing, pattern recognition, GAs, volatile organic compounds) [228] • spectroscopy in clinical chemistry, using chemometric calibration techniques [245] infrared spectroscopy The appl. of single-pass attenuated total reflectance Fourier transform • for protein analysis [430] Inherent Safety in Process Plant Design - An IndexBased Appr. [233] Innate Intelligence for Artificial Organisms: via Species Evol. of Neural Networks [279] insertion Characterisation and opt. of hybrid • devices using GAs [237] in situ Mid-infrared biospectroscopic analysis of biological syst. in vitro and • [274] Inspection Three Dimensional T-ray • Syst. [467] Instruction sch. using GAs [451] Instrumentation Soft Computing Methods for Cntr. and • [243] Integrated field modeling [315] inteligente Estudio de la coordinación • en robots b´ıpedos: aplicaci´ on de l´ ogica borrosa y algoritmos gen´ eticos [41] Intelligence A Review of Artificial • techniques Appl. to Protein Structure Prediction [239] – Computational • in Software Quality Assurance [459] – Evol. alg. and emergent • [365] – Evol. Alg. in Artificial • A Comparative Study Through Appl. [495] – Evolving Artificial • [233] – Innate • for Artificial Organisms: via Species Evol. of Neural Networks [360] Intelligent Automated Electric Distribution Syst. Planning Using • Methods and Geographic Info System [247] – Evolving • musical materials [474] • behavior as an adaptation to the task environment [579] • cntr. based on fuzzy alg. and GAs [220] interaction A dynamical model of the distr. • of intracellular signals [503] – Computer simulation of gen. adaptation: Par. subcomponent • in a multilocus model [392] – Determination of 3D structure of suramin in solution and model of • of suramin with basic fibroblast and plateletderived growth factors [265] – Multivariate NIR Studies of Seed-Water • in Scots Pine Seeds (Pinus sylvestris L.) [543] – The evol. of learning: Simulating the • of adaptive processes [548] Inter-GEN A hybrid appr. to eng. design opt. [271] Internet DJM: Distr. Java Machine for • computing [33] Internet-based A Design Tool Architecture for the Rapid Evaluation of Product Design Tradeoffs in an • Syst. Modeling Environment [572] interpretation Automated image segmentation and • using GAs and semantic nets [563] – Induktiivinen oppiminen metsänviljelyn tietokannan tulkinnassa [Inductive learning in • of databases of forest cultivation] [447] • modeling and forecasting runoff of regional hydrogeologic syst. [403] interstellar GAs, pulsar planets, and ionized • microturbulence [220] intracellular A dynamical model of the distr. interaction of • signals [131] introduction An • to GAs [304] invariant Thedetermination of • parameters and operators of the traditional GA using an adaptive gen. alg. generator [280] Invariants Approximation Alg. for Some Topological • of Graphs [217] inversion Broadband nonlinear • for geoacoustic parameters in shallow water [262] – Two-dimensional time-domain • of perfect conductors using the GA [133] Investigating GAs for sch. [174] investigation An • of diploid GAs for adaptive search on nonstationary functions [416] – An • of Supervised Learning in Gen. Prog. [407]

44

– An • of the applicability of GAs to spacecraft trajectory opt. [326] • on the Appl. of GAs to the Load Flow Problem in Electrical Power Syst. [237] in vitro Mid-infrared biospectroscopic analysis of biological syst. • and in situ [248] involving Response surface methods for experiments • correlated noise variables [403] ionized GAs, pulsar planets, and • interstellar microturbulence [413] Irr´ eguli` eres Alg. Heuristiques et Evol. nistes: Appl. à la R´ esolution du Probl´ eme de Placement de Formes • [356] irrigated Decision support for • project planning using a GA [390] irrigation Opt. of seasonal • sch. by GAs (adaptive penalty) [458] iterated Stochastic • gen. hillclimbing [439] Iterative and Hierarchical Methods for Codebook Generation in Vector Quantization [330] – Remapping hyperspace and subpartition sampling in • gen. search [37] jakorajaoptimointi Multi-objective Reconfiguration of Medium Voltage Distribution Networks [Keskij¨ anniteverkkojen kytkent¨ atilanteen monitavoitteinen • [271] Java DJM: Distr. • Machine for Internet computing [192] Job Par. GAs for Single Machine • Sch. with Earliness and Tardiness Penalties [455] Job Scheduling GAs and • [301] job shop scheduling An architechture for • with GAs [386] Job Shops On Merging Sequencing and Sch. Theory with GAs to Solve Stochastic • [402] Job-Shop Scheduling GA-Based Sch. Syst. for Dynamic • Problems [273] Josephson Junction Cntr. of Quantum Evol. and • circuits [12] kannusteratkaisun Computation of Incentive Stackelberg Solution [Stackelbergin pelin • laskeminen] [14] katsaus Geneesys – • kolmiulotteiseen keinoelämään nyt ja hahmotelma tulevaisuudesta [A Review of 3D AL and Outline of its Future] [16] kehitt¨ aminen Loistehon säätömodulin • [Developing of the Reactive Power Cntr. ] [20] – MILP-menetelmien • [Developing MILP-methods] [110] – Rasterointimenetelmän • mustesuihkutulostimelle geneettisell¨ a algoritmilla [14] keinoel¨ am¨ a¨ an Geneesys – katsaus kolmiulotteiseen • nyt ja hahmotelma tulevaisuudesta [A Review of 3D AL and Outline of its Future] [28] keinotekoinen Neuroevol. Based Artificial Bandwidth Expansion of Telephone Band Speech [Neuroevoluutiopohjainen puhelinpuheen taajuuskaistan • laajentaminen] [82] Kern Ein • f¨ ur genetisches Prog. mieren in C++ [Gen. prog. kernel in C++] [82] kernel Ein Kern f¨ ur genetisches Prog. mieren in C++ [Gen. prog. • in C++] [37] Keskij¨ anniteverkkojen Multi-objective Reconfiguration of Medium Voltage Distribution Networks • kytkent¨ atilanteen monitavoitteinen jakorajaoptimointi] [485] key-board Experimentation with an adaptive search strategy for solving a • design/configuring problem [525] Kinematic motion planning for redundant robots using GAs [372] kinetics Modeling of metabolic syst. using fuzzy logic and supervisory simplex GA (enzyme • Escherichia coli, glycolysis, tricarboxylic acid cycle) [496] KL-ONE A study of par. and prog. in classifier syst. and its appl. to classification in • semantic networks [584] knowledge GA with qualitative • enchancement for layout design under continuous space formulation [336] – Incorporation of • in gen. recombination [226] • Discovery for Female Urinary Incontinence Expert Syst. [522] knowledge-based Xroute: A • routing syst. using neural networks and GAs [517] knowledge-intensive Inductive learning of decision rules from attribute-based examples: A • GA appr. [14] kolmiulotteiseen Geneesys – katsaus • keinoelämään nyt ja hahmotelma tulevaisuudesta [A Review of 3D AL and Outline of its Future] [578] kombinatorischen Evol. und Opt. : Ein populationsgenetischer Zugang zu • Optimierungsproblemen [368]


Kombinierte Touren- und Standortplanung bei der Hausm¨ ullentsorgung mit einem evol. sstrategischen Ansatz [215] Komitees Problemlösung durch • neuronaler Netze [151] Kommunikationsaufwand Auslegung eines Rechnernetzwerkes mit minimalem • mittels evol. ¨ arer Algorithmen [186] Kommunikationstopologie Einfluß der • auf massiv par. e Genetische Algorithmen [126] Konfigurierung Evaluierung, Parametrisierung und • genetischer Algorithmen [160] Konnektionistischer Genetische Algorithmen zur Opt. • Modelle [134] konstruktionen Opt. e dimensionierung technischer • [469] Kontinuierliche Regenerierung von ATP f¨ ur enzymatische Synthesen [113] Konvergenzverhalten Das • von ESn [165] – Einfluß verschiedener Wahrscheinlichkeitsverteilungen auf das • von ESn [100] Konzepte zur Parallelisierung genetischer Algorithmen [253] kraft Incorporation of environmental, economic and production quality criteria in multiobjective eng. design of chlorine/chlorine dioxide softwood • pulp bleaching processes [183] Kynernetische Evolution als Strategie der experimellen Forschung in der Str¨ omungstechnik [37] kytkent¨ atilanteen Multi-objective Reconfiguration of Medium Voltage Distribution Networks [Keskij¨ anniteverkkojen • monitavoitteinen jakorajaoptimointi] [93] kytst A Study on the Use of GAs in Project Time Sheduling [Tutkimus geneettisten algoritmien • projektin aikataulutuksessa] [28] laajentaminen Neuroevol. Based Artificial Bandwidth Expansion of Telephone Band Speech [Neuroevoluutiopohjainen puhelinpuheen taajuuskaistan keinotekoinen • [321] l’alignement Développement de méthodes besées sur les math´ ematiques, l’informatique et l’intelligence artificielle pour • de s´ equences et la pr´ ediction de structures prot´ eines [Development of mathematical, computing and artificial intelligence methods for the protein secondary structure prediction] [370] Landscapes Evol. Alg. , Fitness • and Search [147] language Gen. nat. • processing [473] large-scale GAs and the satisfiability of • Boolean expressions [12] laskeminen Computation of Incentive Stackelberg Solution [Stackelbergin pelin kannusteratkaisun • [173] Lastflußoptimierung Evol. sstrategische • [111] lattice model Protein folding problem, An Alg. • appr. [334] layer GAs for partitioning, placement, and • assignment for multichip modules [584] layout GA with qualitative knowledge enchancement for • design under continuous space formulation [158] – GAs in • sel. for tree-like pipe networks [340] – Towards opt. circuit • using advanced search techniques [193] Layoutproblems Verbesserung des Simulated Annealing unter Anwendung Genetischer Programmierung am Beispiel des Diskreten Quadratischen • [144] Layout-Synthese Chip-Assembly Strategien bei der • nach Floorplan-Vorgaben [181] learn Evol. principles in self-referential learning, or on learning how to • the meta-meta-...hook [564] learning A computational theory of • in distr. syst. [562] – A • syst. based on gen. adaptive alg. [310] – Alg. for comb. opt. in real-time and their automated refinements by gen. -based • [416] – An Investigation of Supervised • in Gen. Prog. [73] – Applying GAs to recurrent neural networks for • network parameters and architecture [400] – Aprendizaje de reglas difusas usando algoritmos gen´ eticos [Concept • trought GAs] [155] – Classifier syst. • of the Boolean multiplexer function [466] – Cognitive Maps in • CSs [523] – Computational modeling of evol. • [499] – Computer-aided gas pipeline operation using GAs and rule • [550] – Default hierarchy formation and memory exploitation in • classifier syst. [129] – Discovery • in autonomous agents using GAs [290] – Embodied Evol. of • Ability [558] – Empirical studies of default hierarchies and sequences of rules in • classifier syst. [127]


– Evol. principles in self-referential • or on • how to learn: the meta-meta-...hook [405] – Hierarchical • with Procedural Abstraction Mechanisms [517] – Inductive • of decision rules from attribute-based examples: A knowledge-intensive GA appr. [563] – Induktiivinen oppiminen metsänviljelyn tietokannan tulkinnassa [Inductive • in interpretation of databases of forest cultivation] [512] – Neural network and gen. • alg. for computer-aided design and pattern recognition [516] • Boolean functions with GAs: A PAC analysis [404] • gene linkage to effectively solve problems of bounded difficulty using GAs (problem solving, stochastic opt. ) [94] • the structure of neural networks using GAs [490] – Opt. , • and Nat. Alg. [96] – Parameter Evaluation and Gen. -Based Rule • for the Differential Diagnosis of Female Urinary Incontinence [30] Learning Taitoa vaativien tehtävien oppiminen ja suoritus WorkPartner-robotilla • and performing skill demanding tasks with WorkPartner robot] [543] learning The evol. of • Simulating the interaction of adaptive processes [528] – The impact of data structures on the perf. of gen. -alg. -based • [354] – Zeroth-Order Shape Opt. Utilizing a • Classifier Syst. [510] Leichtbaufachwerken FormOpt. von • durch Einsatz einer ESs [196] Leichtbaustrukturen Untersuchung zur Anwendung eines Verfahrens der ES bei der Opt. von • [207] lentiviral Butterfly oviposition behavior, pika biogeography, and • seuence evol. [441] level Operational and Tactical • Opt. in Printed Circuit Board Assembly [15] Library Alg. • for Large Scale Vehicle Routing [281] LiDAR An Adaptive Computer Vision Technique for Estimating the Biomass and Density of Loblolly Pine Plantations using Digital Orthophotography and • Imagery [14] Life Geneesys – katsaus kolmiulotteiseen keinoelämään nyt ja hahmotelma tulevaisuudesta [A Review of 3D Artificial • and Outline of its Future] [394] ligand The design of a • discovery and opt. syst. for structure-based drug design [454] ligation A GA for non-enzymic template-directed • of RNA oligomers [227] light Adaptive cntr. of the propagation of ultrafast • through random and nonlinear media [425] limitations Appl. and • of GAs for the opt. of multivariate calibration techniques [223] Linear Quantum Info Processing and its • Optical Impl. [321] l’informatique Développement de méthodes besées sur les math´ ematiques, • et l’intelligence artificielle pour l’alignement de s´ equences et la pr´ ediction de structures prot´ eines [Development of mathematical, computing and artificial intelligence methods for the protein secondary structure prediction] [404] linkage Learning gene • to effectively solve problems of bounded difficulty using GAs (problem solving, stochastic opt. ) [321] l’intelligence Développement de méthodes besées sur les math´ ematiques, l’informatique et • artificielle pour l’alignement de s´ equences et la pr´ ediction de structures prot´ eines [Development of mathematical, computing and artificial intelligence methods for the protein secondary structure prediction] [580] living Computer simulation of a • cell [346] Load Cell GA Opt. of • Geometry by Finite Element Analysis [326] Load Flow Problem Investigation on the Appl. of GAs to the • in Electrical Power Syst. [348] loading Discrete opt. of structures under dynamic • by using sequential and par. evol. strategies [281] Loblolly An Adaptive Computer Vision Technique for Estimating the Biomass and Density of • Pine Plantations using Digital Orthophotography and LiDAR Imagery [221] Local Search and Variable Neighborhood Search Alg. for the Vehicle Routing Problem with Time Windows [44] • structure opt. in evol. generated neural network architectures [409] – Opt. with evol. alg. and • search [305] local search Adaptive global opt. with •

[181]

45

[195] [179]

– Gen. • A pop. -based search alg. locate Using multiple searches to • a randomly moving target

lockermaterialien Opt. von Saugkopfeinläufen zur gewinnung mariner • mit hilfe der evol. sstrategischen Experimentiertechnik [288] Logic From the Cntr. of Quantum Syst. to Multiqubit • [225] Logic Synthesis Distr. Gen. Prog. Models with Appl. to • on FPGAs [16] Loistehon säätömodulin kehittäminen [Developing of the Reactive Power Cntr. ] [65] Lokale Selbstanpassung von Parametern massiv par. er genetischer Alg. en [571] Long-range predictability of high-dimensional chaotic dynamics [68] Losgr¨ ossenoptimierung Einsatz Genetischer Algorithmen zur • [271] Machine DJM: Distr. Java • for Internet computing [408] – Evol. Prog. Induction of Binary • Code and its Appl. [192] – Par. GAs for Single • Job Sch. with Earliness and Tardiness Penalties [343] machine learning A comparison of GAs and other • syst. on a complex classification task from common disease research [150] – A methodology for software cost estimation using • techniques [476] – GA based • appl. to the dynamic routing of discrete parts [576] – GAs in • and opt. [498] • procedures for generating image domain feature detectors [457] • with rule extraction by gen. assisted reinforcement REGAR: Appl. to nonlinear cntr. [542] Machine Learning On GAs in • and Opt. [565] machine learning Some experiments in • using vector evaluated GAs [448] Macro A GA for Mixed • and Standard Cell Placement that Directly Incorporates Cell Membership Info [32] Management Searching for Prescriptive Treatment Schedules with a GA: A tool for Forest • [184] Manipulating subpop. of feasible and infeasible solutions in GAs [109] manufacturer A finite capacity sch. syst. for a silicon wafer • [Hienokuormitusjrjestelm piikiekkovalmistajalle] [462] manufacturing A multi-objective simulation opt. method using a GA with appl. in • [295] – A • process planning model using GAs [103] – Applying Soft Computing in • [Pehmolaskennan soveltaminen tehdasymp¨ arist¨ oss¨ a] [481] – GAs and neural networks appl. to • sch. [426] mapping Computational methods for the opt. of the • of actuators and sensors in the cntr. of flexible structures [83] – FEM Mesh • to a SIMD Machine Using GAs [505] mariner Opt. von Saugkopfeinläufen zur gewinnung • lockermaterialien mit hilfe der evol. sstrategischen Experimentiertechnik [11] marketing On finding opt. potential customers from a large • database – A GA appr. [186] massiv Einfluß der Kommunikationstopologie auf • par. e Genetische Algorithmen [401] – Globale Opt. mit • par. en genetischen Algorithmen [65] – Lokale Selbstanpassung von Parametern • par. er genetischer Alg. en [501] Massively GAs and Pop. Structures — A • Par. Alg. [141] – GAs and pop. structures. A • par. alg. [396] – Simulation of condensed-phase physical, chemical, and biological syst. on • par. computers (free energy perturbation, MIMD,malate dehydrogenase, enzymes, GA) [555] matching Two-dimensional and three-dimensional model-based • using a minimum Rep. criterion and a hybrid GA [407] material Chemometrics in spectroscopic near infrared imaging for plastic • recognition [486] – Opt. balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical shells in reinforced concrete including elastic and plastic • behaviour] [247] materials Evolving intelligent musical • [321] math´ ematiques Développement de méthodes besées sur les • l’informatique et l’intelligence artificielle pour [505]

46

l’alignement de s´ equences et la pr´ ediction de structures prot´ eines [Development of mathematical, computing and artificial intelligence methods for the protein secondary structure prediction] [321] mathematical Développement de méthodes besées sur les math´ ematiques, l’informatique et l’intelligence artificielle pour l’alignement de s´ equences et la pr´ ediction de structures prot´ eines [Development of • computing and artificial intelligence methods for the protein secondary structure prediction] [492] – Relapse from tobacco smoking cessation: • and computer micro-simulation modelling including parameter opt. with GAs [371] mathematische Aspekte genetischer Opt. salg. en: • Modellierung und Einsatz in der Fahrplanerstellung [471] mathematischen Ein Evolutionsverfahren zur • Modellierung station¨ arer Zust¨ ande in dynamischen Systemen [349] MathEvolvica – Simulierte Evol. von Entwicklungsprog. men der Natur [39] Matkapuhelinantennien GA opt. of antennas for mobile terminals • optimointi geneettisell¨ a algoritmilla] [242] MCASE Studies in appl. computational chemistry: META model of photochemical reactions under UV under nat. conditions and an • appr. to the search of a cure for Parkinson’s disease [98] Measurement Gen. Prog. Techniques Appl. to • Data [218] Measuring evol. testability of real-time software [308] mechanical GA based non-linear modeling and its appl. to cntr. and • diagnostics [276] – New Metrological Techniques for • Characterization at the Microscale and Nanoscale [405] Mechanisms Hierarchical Learning with Procedural Abstraction • [434] – Searching for chemical reaction • with GAs [227] media Adaptive cntr. of the propagation of ultrafast light through random and nonlinear • [37] Medium Multi-objective Reconfiguration of • Voltage Distribution Networks [Keskij¨ anniteverkkojen kytkent¨ atilanteen monitavoitteinen jakorajaoptimointi] [170] mehrgliedrigen Alg. en zur Parameteradaption in der • ES bei der diskreten Opt. [182] mehrgliedriger Untersuchungen zur Effizienz • asynchroner ESn auf Transputersyst. en [448] Membership A GA for Mixed Macro and Standard Cell Placement that Directly Incorporates Cell • Info [232] membrane Computational methods and their appl. for de novo functional protein design and • protein solubilization [236] Memetic Studies on the Theory and Design Space of • Alg. [550] memory Default hierarchy formation and • exploitation in learning classifier syst. [386] Merging On • Sequencing and Sch. Theory with GAs to Solve Stochastic Job Shops [83] Mesh FEM • Mapping to a SIMD Machine Using GAs [209] MESO The evol. structural opt. (ESO) method: Theoretical aspects and the modified evol. ary structural optimization • method [489] messy Binary and floating-point function opt. using • GAs [163] – Generalizations and par. ization of • GAs and communication in parallel gen. alg. [363] – Search, polynomial complexity, and the fast • GAs [242] META Studies in appl. computational chemistry: • model of photochemical reactions under UV under nat. conditions and an MCASE appr. to the search of a cure for Parkinson’s disease [372] metabolic systems Modeling of • using fuzzy logic and supervisory simplex GA (enzyme kinetics, Escherichia coli, glycolysis, tricarboxylic acid cycle) [91] metal forming A heating process alg. for • by a moving heat source [181] meta-meta-...hook Evol. principles in self-referential learning, or on learning how to learn: the • [119] metaphors Biological • and the design of modular artificial neural networks [433] Metastrategien Grundlegende empirische Untersuchungen der Parameter von ESn — • [339] methodologies Cntr. and Operational • for EnergyEfficient Operation of Building HVAC syst. [320] methodology A gen. • for configuration design


– A • for software cost estimation using machine learning techniques [345] – Using GAs as an automated • for conceptual design of rotorcraft [276] Metrological New • Techniques for Mechanical Characterization at the Microscale and Nanoscale [563] mets¨ anviljelyn Induktiivinen oppiminen • tietokannan tulkinnassa [Inductive learning in interpretation of databases of forest cultivation] [417] microclusters The structural opt. of atomic and molecular • using a GA in real-valued space-fixed coordinates [276] Microscale New Metrological Techniques for Mechanical Characterization at the • and Nanoscale [492] micro-simulation Relapse from tobacco smoking cessation: Mathematical and computer • modelling including parameter opt. with GAs [403] microturbulence GAs, pulsar planets, and ionized interstellar • [269] microwave Electromagnetic physical modeling of • devices and circuits [444] – Guided-mode resonance reflection and transmission filters in the optical and • spectral ranges [237] Mid-infrared biospectroscopic analysis of biological syst. in vitro and in situ [275] Migration Adaptation Through Stochastic Evol. Neuron • Process [509] Mikrorechners Der Einsatz eines • zur hybriden Opt. und Schwingungsanalyse [20] MILP-menetelmien kehittäminen [Developing MILP-methods] [20] MILP-methods MILP-menetelmien kehitt¨ aminen [Developing • [553] MIMD Gen. neural networks on • computers [396] MIMD,malate Simulation of condensed-phase physical, chemical, and biological syst. on massively par. computers (free energy perturbation, • dehydrogenase, enzymes, GA) [151] minimalem Auslegung eines Rechnernetzwerkes mit • Kommunikationsaufwand mittels evol. ¨ arer Algorithmen [546] minimization Drag • on a body of revol. [384] – Robust Sensor Fusion Alg. : Calibration and Cost • [191] minimum A GA for the • spanning tree problem [555] – Two-dimensional and three-dimensional model-based matching using a • Rep. criterion and a hybrid GA [169] mission GAs appl. to a • routing problem [448] Mixed A GA for • Macro and Standard Cell Placement that Directly Incorporates Cell Membership Info [250] Mixture-process experiments with cntr. and noise variables [39] mobile GA opt. of antennas for • terminals [Matkapuhelinantennien optimointi geneettisell¨ a algoritmilla] [220] model A dynamical • of the distr. interaction of intracellular signals [295] – A manufacturing process planning • using GAs [581] – A stochastic generalization of Eigen’s • of nat. sel. [503] – Computer simulation of gen. adaptation: Par. subcomponent interaction in a multilocus • [392] – Determination of 3D structure of suramin in solution and • of interaction of suramin with basic fibroblast and platelet-derived growth factors [234] – Efficient • fitting using a GA: pole-zero approximations of HRTFs [27] – Parameter Estimation of a Plucked String Synthesis • via the GA [547] – Simulation of a cell-assembly • [242] – Studies in appl. computational chemistry: META • of photochemical reactions under UV under nat. conditions and an MCASE appr. to the search of a cure for Parkinson’s disease [399] – The Design and Analysis of a Computational • of Cooperative Coevol. [22] – VALMA-annoslaskentamallin rajoitettu optimointi geneettisell¨ a algoritmilla [Constrained Opt. of the VALMA Dose Assessment • by a GA] [355] model-based An EP appr. to probabilistic • fault diagnosis of chemical processes [555] – Two-dimensional and three-dimensional • matching using a minimum Rep. criterion and a hybrid GA [260] modeles Etude sur la generation de • de structures secondaires pour la prediction de structures proteiques [150]


Modeling A Design Tool Architecture for the Rapid Evaluation of Product Design Tradeoffs in an Internet-based Syst. • Environment [411] – Biologically driven molecular • for anticonvulsant drug design [231] – Coevol. Fuzzy • [523] – Computational • of evol. learning [269] – Electromagnetic physical • of microwave devices and circuits [308] – GA based non-linear • and its appl. to cntr. and mechanical diagnostics [243] – Integrated field • [447] – Interpretation, • and forecasting runoff of regional hydrogeologic syst. [431] – Neural and Evol. Computing in • of Complex Syst. [261] • and decision-making in a semiconductor supply chain [372] • of metabolic syst. using fuzzy logic and supervisory simplex GA (enzyme kinetics, Escherichia coli, glycolysis, tricarboxylic acid cycle) [361] – Process cntr. , opt. , and • of chemical syst. using GAs and neural networks [203] – Spectroscopic • and analysis of plasma conditions in implosion cores [160] Modelle Genetische Algorithmen zur Opt. Konnektionistischer • [115] Modelle Opt. gravimetrischer • mit der ES [371] Modellierung Aspekte genetischer Opt. salg. en: mathematische • und Einsatz in der Fahrplanerstellung [471] Modellierung Ein Evolutionsverfahren zur mathematischen • station¨ arer Zust¨ ande in dynamischen Systemen [238] modelling Aspects of • and simulation of GAs: a formal appr. [492] – Relapse from tobacco smoking cessation: Mathematical and computer micro-simulation • including parameter opt. with GAs [381] – Universal Service: Issues on • and Regulation [235] models Automated Formulation of Opt. • for Steel Beam Structures [225] – Distr. Gen. Prog. • with Appl. to Logic Synthesis on FPGAs [132] – GAs, their appl. and • in nonlinear syst. ident. [358] – Opt. of quantitative variables in discrete event simulation • [210] – Simple • of protein and small molecule syst. [585] – The opt. of simulation • by GAs: A comparative study [171] Modified Uniform Crossover and Desegredation in GAs [209] – The evol. structural opt. (ESO) method: Theoretical aspects and the • evol. ary structural optimization (MESO) method [119] modular Biological metaphors and the design of • artificial neural networks [211] – On Evolving • Neural Networks [307] – Theory and appl. of • reconfigurable robotic syst. [411] molecular Biologically driven • modeling for anticonvulsant drug design [338] – Computer-assisted drug design: GAs and structures of • clusters of aromatic hydrocarbons and actinomycin Ddeoxyguanosine [379] – Global opt. appl. to • architecture [541] – Global Opt. for Articulated Figures: • Structure Prediction and Motion Synthesis for Animation [417] – The structural opt. of atomic and • microclusters using a GA in real-valued space-fixed coordinates [420] molecular docking Computational biology: Methods in automated • with appl. in industrial virology and antibodyantigen recognition [210] molecule Simple models of protein and small • syst. [37] monitavoitteinen Multi-objective Reconfiguration of Medium Voltage Distribution Networks [Keskij¨ anniteverkkojen kytkent¨ atilanteen • jakorajaoptimointi] [46] monitoring Eine Entwicklungsumgebung zum Monitoring Genetischer Algorithmen [A development tool for • GAs] [46] Monitoring Eine Entwicklungsumgebung zum • Genetischer Algorithmen [A development tool for monitoring GAs] [484] Monte Carlo validation of two gen. clustering alg. [142] Monte-Carlo-Generator-Parametern Opt. von • mit Genetischen Algorithmen [33]

47

moottoroidun Geneettisen algoritmin soveltaminen • hengityksensuojaimen toimintaparametrien optimointiin [541] Motion Global Opt. for Articulated Figures: Molecular Structure Prediction and • Synthesis for Animation [525] – Kinematic • planning for redundant robots using GAs [208] Motivated On Solution Appr. for Some Industrially • Comb. Opt. Problems [59] motors Structural opt. of cage induction • using finite element analysis [91] moving A heating process alg. for metal forming by a • heat source [179] – Using multiple searches to locate a randomly • target [52] MPGA Partielle Auswertung der Zielfunktion eines • [34] Multi reslution dental image registration based on GAs [334] multichip modules GAs for partitioning, placement, and layer assignment for • [327] Multicriteria structural opt. by GA [479] multicriterion Gen. search methods for • opt. design of viscoelastically damped structures [549] Multidimensional Analysis and Appl. of Darwinian opt. Alg. in the • Spaces [303] multi-dimensional Heuristic recombination operators for • decision problems [137] multi-heuristic GAs for the development of real-time • search strategies [503] multilocus Computer simulation of gen. adaptation: Par. subcomponent interaction in a • model [125] multimodal GAs in • function opt. [291] Multi-Modality A Novel Automated Appr. of • Retinal Image Registration and Fusion [23] multiobjective A • appr. appl. to the protein structure prediction problem [462] multi-objective A • simulation opt. method using a GA with appl. in manufacturing [373] Multiobjective An Empirical Study of Evol. Techniques for • Opt. in Eng. Design [452] – Evol. Alg. for • Opt. : Methods and Appl. [251] – Explicit building-block • GAs: Theory, analysis, and development [253] – Incorporation of environmental, economic and production quality criteria in • eng. design of chlorine/chlorine dioxide softwood kraft pulp bleaching processes [366] • GAs with Appl. to Cntr. Eng. Problems [37] Multi-objective Reconfiguration of Medium Voltage Distribution Networks [Keskij¨ anniteverkkojen kytkent¨ atilanteen monitavoitteinen jakorajaoptimointi] [286] Multiple Evaluating the Spatial Ecology of Anthrax in North America: Examining Epidemiological Components Across • Geographic Scales Using a GIS-Based Appr. [139] – Evaluation of Hybrids of Hill Climbing and GAs for • Fault Diagnosis [64] – GAs and • Distinct Solutions [155] multiplexer Classifier syst. learning of the Boolean • function [288] Multiqubit From the Cntr. of Quantum Syst. to • Logic [425] multivariate Appl. and limitations of GAs for the opt. of • calibration techniques [265] • NIR Studies of Seed-Water Interaction in Scots Pine Seeds (Pinus sylvestris L.) [95] muodon Diesel-moottorin nokka-akselin • optimointi geneettisell¨ a algoritmilla [Diesel engine cam shape design by GA] [410] musical A hybrid neuro-gen. pattern evol. syst. appl. to • composition [247] – Evolving intelligent • materials [110] mustesuihkutulostimelle Rasterointimenetelmän kehitt¨ aminen • geneettisell¨ a algoritmilla [427] Mutation The Role of • and Recombination Evol. Alg. [264] mutation operators Novel • and their appl. to regularization of artificial neural networks [69] Myoelectric signal recognition using gen. prog. [418] na Algoritmo genético construtivo • otimiza¸cão de problemas combinatoriais de agrupamentos [175] Nachrichtentechnik Untersuchung u ¨ ber die Anwendbarkeit der ES in der • [276] Nanoscale New Metrological Techniques for Mechanical Characterization at the Microscale and • [475] nat ESn zur numerischen Lösung von Adaptationsaufgaben (Dr. rer. • [42]

48

Natur MathEvolvica – Simulierte Evol. von Entwicklungsprog. men der • [581] natural A stochastic generalization of Eigen’s model of • sel. [147] – Gen. • language processing [490] – Opt. , Learning and • Alg. [242] – Studies in appl. computational chemistry: META model of photochemical reactions under UV under • conditions and an MCASE appr. to the search of a cure for Parkinson’s disease [199] Near-optimal triangulation of a point set using GAs [221] Neighborhood Local Search and Variable • Search Alg. for the Vehicle Routing Problem with Time Windows [572] nets Automated image segmentation and interpretation using GAs and semantic • [331] network An appr. to a problem in • design using GAs [73] – Applying GAs to recurrent neural networks for learning • parameters and architecture [419] – Opt. of signal processing and • cntr. in telecommunications syst. [582] – Opt. of transportation • design problems using a cumulative GA and neural networks [496] networks A study of par. and prog. in classifier syst. and its appl. to classification in KL-ONE semantic • [158] – GAs in layout sel. for tree-like pipe • [37] – Multi-objective Reconfiguration of Medium Voltage Distribution • [Keskij¨ anniteverkkojen kytkent¨ atilanteen monitavoitteinen jakorajaoptimointi] [215] Netze Problemlösung durch Komitees neuronaler • [412] neural Evol. of structures - Optimization of artificial • structures for info processing [431] • and Evol. Computing in Modeling of Complex Syst. [507] neural nets Coding strategies for GAs and • [299] neural network GANNet: A GA for searching topology and weight spaces in • design. The first step in finding • solution [44] – Local structure opt. in evol. generated • architectures [512] • and gen. learning alg. for computer-aided design and pattern recognition [329] • synthesis using cellular encoding and the GA [50] Neural Network Observing, Understanding, and cntr. the Gen. Method on a • Appl. [422] neural networks Appl. of • and GAs in high energy physics [73] – Applying GAs to recurrent • for learning network parameters and architecture [119] – Biological metaphors and the design of modular artificial • [51] Neural Networks Combining GAs and • The Encoding Problem [194] neural networks Computational complexity of • and CSs [104] – Evol. design of • [66] – Evolving sequential • for time series forecasting [561] – GAs and fitness variance with an appl. to the automated design of artificial • [481] – GAs and • appl. to manufacturing sch. [172] – GAs and • for opt. of hydro power production [117] – GAs for automatic design of artificial • [553] – Gen. • on MIMD computers [233] Neural Networks Innate Intelligence for Artificial Organisms: via Species Evol. of • [94] neural networks Learning the structure of • using GAs [264] – Novel mutation operators and their appl. to regularization of artificial • [504] – Nuclear power plant fault diagnostics and thermal perf. studies using • and GAs [211] Neural Networks On Evolving Modular • [527] neural networks Opt. groundwater remediation using artificial • and the GA [582] – Opt. of transportation network design problems using a cumulative GA and • [361] – Process cntr. , opt. , and modeling of chemical syst. using GAs and • [522] – Xroute: A knowledge-based routing syst. using • and GAs [57] – Structural opt. of feedforward • using GA [391] Neural Networks Symbiotic Evol. of • in Sequential Decision Tasks [349]


[187, 188] – Using • and GAs as Heuristics for NP-Complete Problems [28] Neuroevolution Based Artificial Bandwidth Expansion of Telephone Band Speech [Neuroevoluutiopohjainen puhelinpuheen taajuuskaistan keinotekoinen laajentaminen] [28] Neuroevoluutiopohjainen Neuroevol. Based Artificial Bandwidth Expansion of Telephone Band Speech • puhelinpuheen taajuuskaistan keinotekoinen laajentaminen] [410] neuro-genetic A hybrid • pattern evol. syst. appl. to musical composition [275] Neuron Adaptation Through Stochastic Evol. • Migration Process [215] neuronaler Problemlösung durch Komitees • Netze [319] neuro-nester Gen. • [414] neutron spectrum GAs: a new technique for solving the • unfolding problem [254] News and Trading Rules [62] NFS Ein adaptives Syst. zur Opt. von • [544] niche Experimental study of speciation in ecological • theory using GAs [367] Nichingmethods for GAs [456] nichtlineare Optimieren mit ESn: Reihenfolgeprobleme, • und ganzzahlige Opt. [265] NIR Multivariate • Studies of Seed-Water Interaction in Scots Pine Seeds (Pinus sylvestris L.) [341] – An evaluation of the GA as a computational tool in protein • [450] – Using numerical methods and artificial intelligence in • data processing and analysis [250] noise Mixture-process experiments with cntr. and • variables [248] – Response surface methods for experiments involving correlated • variables [95] nokka-akselin Diesel-moottorin • muodon optimointi geneettisell¨ a algoritmilla [Diesel engine cam shape design by GA] [168] nonbinary Walsh function analysis of GAs of • strings [428] Non-Convex A GA for a Three-Dimensional • Bin Packing Problem [388] nondestructive Signal processing and image restoration techniques for two-dimensional eddy current • evaluation [454] non-enzymic A GA for • template-directed ligation of RNA oligomers [227] nonlinear Adaptive cntr. of the propagation of ultrafast light through random and • media [515] – Biologically Influenced Alg. and Par. in • Opt. [217] – Broadband • inversion for geoacoustic parameters in shallow water [308] non-linear GA based • modeling and its appl. to cntr. and mechanical diagnostics [432] nonlinear GAs appl. to • and complex domains [132] – GAs, their appl. and models in • syst. ident. [457] – Machine learning with rule extraction by gen. assisted reinforcement REGAR: Appl. to • cntr. [369] • adaptive filtering: The GA appr. [529] – Parameter estimation for • syst. [435] – Training based opt. of • digital filters: Case studies [497] Non-linearities in gen. adaptive search [174] nonstationary An investigation of diploid GAs for adaptive search on • functions [286] North America Evaluating the Spatial Ecology of Anthrax in • Examining Epidemiological Components Across Multiple Geographic Scales Using a GIS-Based Appr. [187, 188] NP-Complete Problems Using Neural Networks and GAs as Heuristics for • [504] Nuclear power plant fault diagnostics and thermal perf. studies using neural networks and GAs [450] numerical methods Using • and artificial intelligence in NMR data processing and analysis [567] numerische ES und • Opt. [475] numerischen ESn zur • Lösung von Adaptationsaufgaben (Dr. rer. nat.) [500] nutritional Adaptive behavior of simulated bacterial cells subjected to • shifts [14] nyt Geneesys – katsaus kolmiulotteiseen keinoelämään • ja hahmotelma tulevaisuudesta [A Review of 3D AL and Outline of its Future] [270] object Feature synthesis and analysis by evol. computation for • detection and recognition [383] Objects Generic Evol. Design of Solid • using a GA


Observing Understanding, and cntr. the Gen. Method on a Neural Network Appl. [80] Obstacle Vision-based • Avoidance: A Coevol. Appr. [85] ohjausj¨ arjestelmien Hissien • tilastollinen vertailu [A statistical comparison of two elevator call allocation method] [107] ohjelmien Automaattinen • testaus optimoimalla geneettisill¨ a algoritmeilla [Automatic software testing by opt. with GAs] [454] oligomers A GA for non-enzymic template-directed ligation of RNA • [499] operation Computer-aided gas pipeline • using GAs and rule learning [339] – Cntr. and Operational methodologies for EnergyEfficient • of Building HVAC syst. [577] – Two analysis tools to describe the • of classifier syst. [339] Operational Cntr. and • methodologies for EnergyEfficient Operation of Building HVAC syst. [441] • and Tactical level Opt. in Printed Circuit Board Assembly [81] Operator The Recombination • its Correlation to the Fitness Landscape and Search Perf. [25] operator´ ow Zastosowanie • ewolucyjnych do optymalizacji drzew binarnych [136] operators An evaluation of Holland’s gen. • appl. to a prog. generator [303] – Heuristic recombination • for multi-dimensional decision problems [460] – The time complexity of GAs and the theory of recombination • [304] – Thedetermination of invariant parameters and • of the traditional GA using an adaptive gen. alg. generator [75] opertor Adapting • probabilities in GAs [563] oppiminen Induktiivinen • metsänviljelyn tietokannan tulkinnassa [Inductive learning in interpretation of databases of forest cultivation] [30] – Taitoa vaativien tehtävien • ja suoritus WorkPartnerrobotilla [Learning and performing skill demanding tasks with WorkPartner robot] [443] optical Analysis and opt. design of diffractive • elements [202] – Design and opt. of • diffractive elements using vector space projections and pseudo random encoding [444] – Guided-mode resonance reflection and transmission filters in the • and microwave spectral ranges [223] – Quantum Info Processing and its Linear • Impl. [205] – Rigorous analysis and design of diffractive • elements [442] optics GA opt. methods in geometrical • [244] optimal A stabilized finite element formulation for the • design of forming processes [138] – Adaptive Syst. and the Search for • Index Sel. [443] – Analysis and • design of diffractive optical elements [479] – Gen. search methods for multicriterion • design of viscoelastically damped structures [527] • groundwater remediation using artificial neural networks and the GA [324] • rate concept acquisition using version spaces and GAs [11] – On finding • potential customers from a large marketing database – A GA appr. [340] – Towards • circuit layout using advanced search techniques [134] Optimale dimensionierung technischer konstruktionen [520] Optimieren mit der ES in der Industrie anhand von Beispielen [456] • mit ESn: Reihenfolgeprobleme, nichtlineare und ganzzahlige Opt. [170] Optimierung Alg. en zur Parameteradaption in der mehrgliedrigen ES bei der diskreten • [509] – Der Einsatz eines Mikrorechners zur hybriden • und Schwingungsanalyse [62] Optimierung Ein adaptives Syst. zur • von NFS [557] – Einsatz rechnergest¨ utzter • mittels der ES zur l¨ osung galvanotechnischer Probleme [152] Optimierung Entwicklung von Computer-Algorithmen zur • von Strukturkomponenten nach der Evol. stheorie [578] – Evol. und • Ein populationsgenetischer Zugang zu kombinatorischen Opt. sproblemen [567] – ES und numerische • [556] – ES: • technischer Systeme nach Prinzipien der biologischen Evolution [160] – Genetische Algorithmen zur • Konnektionistischer Modelle [50]

49

[401]

optimierung

Globale • mit massiv par. en genetischen

Algorithmen

Optimierung Optimierung

Globale • mit par. en ESn balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical shells in reinforced concrete including elastic and plastic material behaviour] [43] • digitaler Filter mit genetischen Alg. en [180] • eines Diffusors nach der ES [115] • gravimetrischer Modelle mit der ES [142] • von Monte-Carlo-Generator-Parametern mit Genetischen Algorithmen [505] • von Saugkopfeinl¨ aufen zur gewinnung mariner lockermaterialien mit hilfe der evol. sstrategischen Experimentiertechnik [456] Optimierung Optimieren mit ESn: Reihenfolgeprobleme, nichtlineare und ganzzahlige • [189] Optimierung Par. isierung Genetischer Algorithmen zur Suche und • [140] – Simulation einer unterschaligen Schwebewaage auf einem Analogrechner und • ihres einsschwingverhaltens mit der ES [196] Optimierung Untersuchung zur Anwendung eines Verfahrens der ES bei der • von Leichtbaustrukturen [371] Optimierungsalgorithmen Aspekte genetischer • mathematische Modellierung und Einsatz in der Fahrplanerstellung [198] Optimierungsaufgaben Simulation physikalischer und biologischer Prozesse zur L¨ osung diskreter • [502] Optimierungsprobleme Simulated annealing und ES: Ein vergleich anhand schweriger • [578] Optimierungsproblemen Evol. und Opt. : Ein populationsgenetischer Zugang zu kombinatorischen • [506] Optimierungsverfahren Ein Vergleich von • f¨ ur die zeitdiskrete Simulation [323] optimise The use of GAs to • chemical flowshops of unrestricted topology [38] optimising delta-signa analog-to-digital converter filtering parameters] [164] • flowshop sch. through adaptive GAs [574] optimizations Distr. GAs for function • [470] optimizers GAs as function • [89] optimizing A Description, Analysis, and Comparison of a Hardware and Software Impl. of the SPLASH GA for • symmetric traveling salesman problems [107] – Automaattinen ohjelmien testaus optimoimalla geneettisill¨ a algoritmeilla [Automatic software testing by • with GAs] [24] • GAs for Time Critical Problems [387] • hydrocarbon field development using a GA based appr. (reservoir) [107] optimoimalla Automaattinen ohjelmien testaus • geneettisill¨ a algoritmeilla [Automatic software testing by opt. with GAs] [95] optimointi Diesel-moottorin nokka-akselin muodon • geneettisell¨ a algoritmilla [Diesel engine cam shape design by GA] [17] – Ennakoivaan simulointiin perustuva panostuotannon • [Batch production opt. by evol. computation and predictive simulation] [39] – GA opt. of antennas for mobile terminals [Matkapuhelinantennien • geneettisell¨ a algoritmilla] [84] – Sähkön hankinnan • [Economic dispatch problem, a comparison of some solution methods] [101] – Suurnopeusoikosulkukoneen • [22] – VALMA-annoslaskentamallin rajoitettu • geneettisellä algoritmilla [Constrained Opt. of the VALMA Dose Assessment Model by a GA] [42] optimointiin Geneettisen algoritmin soveltaminen moottoroidun hengityksensuojaimen toimintaparametrien • [49] optimointiteht¨ avien Suurten • ratkaiseminen [Solving large opt. problems] [31] Optimum design of a piezo-feeder based on dynamic analysis [268] • design of cold-formed steel purlins using GAs [25] optymalizacji Zastosowanie operatorów ewolucyjnych do • drzew binarnych [74] orbit Par. • propagation and the analysis of satellite constellations [311] order An empirical computational study of GAs to solve • based problems: An emphasis on TSP and VRPTC [177] [486]

50

– GAs for • dependent processes appl. to robot pathplanning [377] organic Data analysis strategies for qualitative and quantitative determination of • compounds by Fourier transform infrared spectroscopy (signal processing, pattern recognition, GAs, volatile • compounds) [233] Organisms Innate Intelligence for Artificial • via Species Evol. of Neural Networks [185] origin On the • of effective procedures by means of artificial sel. [281] Orthophotography An Adaptive Computer Vision Technique for Estimating the Biomass and Density of Loblolly Pine Plantations using Digital • and LiDAR Imagery [418] otimiza¸ c˜ ao Algoritmo genético construtivo na • de problemas combinatoriais de agrupamentos [45] Ottimizzazione di cavitá RF per acceleratori di particelle [207] oviposition Butterfly • behavior, pika biogeography, and lentiviral seuence evol. [224] oxygen-6-alkylguanine-DNA alkyltransferase Structural studies of the human DNA repair protein • [516] PAC Learning Boolean functions with GAs: A • analysis [206] panels Piezoceramic actuator placement for acoustic cntr. of • [17] panostuotannon Ennakoivaan simulointiin perustuva • optimointi [Batch production opt. by evol. computation and predictive simulation] [438] Paradigm Methods for Statistical Inference: Extending the Evol. Computation • [123] parall` eles Alg. génétiques • pour la planification de trajectoires de robots en environnement dynamique [573] – Allocation de processus sur les architectures • á m´ emoire distribu´ ee [312] parallel A • GA for the set partitioning problem [545] – An analysis of a • GA [503] – Computer simulation of gen. adaptation: • subcomponent interaction in a multilocus model [348] – Discrete opt. of structures under dynamic loading by using sequential and • evol. strategies [178] – Distr. • GAs Dipgal [143] – Efficacy of • GAs [530] – Ein • genetischer Algorithmus f¨ ur das GraphPartitionierungsproblem [526] – Enhanced GAs in constrained search spaces with emphasis in • environments [163] – Generalizations and par. ization of messy GAs and communication in • gen. alg. [501] – GAs and Pop. Structures — A Massively • Alg. [141] – GAs and pop. structures. A massively • alg. [332] – Hierarchical, asynchronous • GAs for simulation-based syst. design [382] – Impl. and Alg. of a Tree Shape • Computer [468] • Ansatz zur L¨ osung des Quadratischen Zuordnungsproblems [162] • GA for the DAG vertex splitting problem [192] • GAs for Single Machine Job Sch. with Earliness and Tardiness Penalties [256] • hierarchical adaptive GA for genome sequencing [54] • impl. of GAs [74] • orbit propagation and the analysis of satellite constellations [300] – Opt. of FIR digital filters using a real parameter • GA and impl. s [396] – Simulation of condensed-phase physical, chemical, and biological syst. on massively • computers (free energy perturbation, MIMD,malate dehydrogenase, enzymes, GA) [493] – The design, analysis, and impl. of • simulated annealing and • GAs for the composite graph coloring problem [92] parallel processors GAs on • [186] parallele Einfluß der Kommunikationstopologie auf massiv • Genetische Algorithmen [472] Parallelen Flowshop Scheduling mit • Genetischen Algorithmen – Eine problemorientierten Analyse genetischer Suchstrategien [401] – Globale Opt. mit massiv • genetischen Algorithmen [177] – Globale Opt. mit • ESn [58] paralleler Ein verteilt • genetischer Algorithmus [166] – Ein • Evolutionsalg. us zur Lösung des Travelling Salesman Problems [487]


– Lokale Selbstanpassung von Parametern massiv • genetischer Alg. en [100] Parallelisierung Konzepte zur • genetischer Algorithmen [189] Parallelisierung Genetischer Algorithmen zur Suche und Opt. [496] parallelism A study of • and prog. in classifier syst. and its appl. to classification in KL-ONE semantic networks [515] – Biologically Influenced Alg. and • in Nonlinear Opt. [328] – Exploitable • in GAs [421] Parallelization Evol. Alg. for Automatic • [163] – Generalizations and • of messy GAs and communication in par. gen. alg. [287] Parameter GAs, • Cntr. and Function Opt. : A New Appr. [433] – Grundlegende empirische Untersuchungen der • von ESn — Metastrategien [529] • estimation for nonlinear syst. [27] • Estimation of a Plucked String Synthesis Model via the GA [96] • Evaluation and Gen. -Based Rule Learning for the Differential Diagnosis of Female Urinary Incontinence [300] – Opt. of FIR digital filters using a real • par. GA and impl. s [492] – Relapse from tobacco smoking cessation: Mathematical and computer micro-simulation modelling including • opt. with GAs [170] Parameteradaption Alg. en zur • in der mehrgliedrigen ES bei der diskreten Opt. [65] Parametern Lokale Selbstanpassung von • massiv par. er genetischer Alg. en [73] parameters Applying GAs to recurrent neural networks for learning network • and architecture [217] – Broadband nonlinear inversion for geoacoustic • in shallow water [38] – [optimising delta-signa analog-to-digital converter filtering • [304] – Thedetermination of invariant • and operators of the traditional GA using an adaptive gen. alg. generator [126] Parametrisierung Evaluierung, • und Konfigurierung genetischer Algorithmen [242] Parkinson’s disease Studies in appl. computational chemistry: META model of photochemical reactions under UV under nat. conditions and an MCASE appr. to the search of a cure for • [45] particelle Ottimizzazione di cavitá RF per acceleratori di • [52] Partielle Auswertung der Zielfunktion eines MPGA [63] partitioning Cntr. • opt. for STOVL aircraft using gen. search methods [334] – GAs for • placement, and layer assignment for multichip modules [342] path Coupler point • synthesis using a hybrid GA [445] – Evol. Appr. to Robot • Planning [294] – The Ariadne’s clew alg. : A general planning technique, Appl. to automatic • planning [487] path-planning GAs for order dependent processes appl. to robot • [410] pattern A hybrid neuro-gen. • evol. syst. appl. to musical composition [512] – Neural network and gen. learning alg. for computeraided design and • recognition [377] pattern recognition Data analysis strategies for qualitative and quantitative determination of organic compounds by Fourier transform infrared spectroscopy (signal processing, • GAs, volatile organic compounds) [103] Pehmolaskennan Applying Soft Computing in Manufacturing • soveltaminen tehdasymp¨ arist¨ oss¨ a] [12] pelin Computation of Incentive Stackelberg Solution [Stackelbergin • kannusteratkaisun laskeminen] [192] Penalties Par. GAs for Single Machine Job Sch. with Earliness and Tardiness • [390] penalty Opt. of seasonal irrigation sch. by GAs (adaptive • [262] perfect Two-dimensional time-domain inversion of • conductors using the GA [347] Performance analysis for GAs [504] – Nuclear power plant fault diagnostics and thermal • studies using neural networks and GAs [528] – The impact of data structures on the • of gen. -alg. -based learning [65]


– The Recombination Operator, its Correlation to the Fitness Landscape and Search • [30] performing Taitoa vaativien tehtävien oppiminen ja suoritus WorkPartner-robotilla [Learning and • skill demanding tasks with WorkPartner robot] [176] permutations Exodus: An extension of the GA to problems dealing with • [318] perspective Analysis of GAs from a global random search method • with techniques for Alg. improvement [396] perturbation Simulation of condensed-phase physical, chemical, and biological syst. on massively par. computers (free energy • MIMD,malate dehydrogenase, enzymes, GA) [17] perustuva Ennakoivaan simulointiin • panostuotannon optimointi [Batch production opt. by evol. computation and predictive simulation] [18] Phase Global Opt. Techniques for IIR • Equalizers [201] phenol Femtosecond time-resolved photoelectron spectroscopy of • [242] photochemical Studies in appl. computational chemistry: META model of • reactions under UV under nat. conditions and an MCASE appr. to the search of a cure for Parkinson’s disease [201] photoelectron Femtosecond time-resolved • spectroscopy of phenol [269] physical Electromagnetic • modeling of microwave devices and circuits [396] – Simulation of condensed-phase • chemical, and biological syst. on massively par. computers (free energy perturbation, MIMD,malate dehydrogenase, enzymes, GA) [508] physicalischer Ein wissensbasierter genetischer Algorithmus zur Rekonstruktion • Ereignisse [198] physikalischer Simulation • und biologischer Prozesse zur L¨ osung diskreter Opt. saufgaben [99] PID-control Geneettisten algoritmien käyttö tutkittaessa sumean logiikan hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the benefit of fuzzy logic for • by means of GAs - case: frequency cntr. ] [99] PID-s¨ a¨ ad¨ oss¨ a Geneettisten algoritmien käyttö tutkittaessa sumean logiikan hy¨ oty¨ a • - Esimerkkin¨ a taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the benefit of fuzzy logic for PID-cntr. by means of GAs - case: frequency cntr. ] [206] Piezoceramic actuator placement for acoustic cntr. of panels [285] Piezoelectric actuator design opt. for shape cntr. of smart composite plate structures [31] piezo-feeder Optimum design of a • based on dynamic analysis [109] piikiekkovalmistajalle A finite capacity sch. syst. for a silicon wafer manufacturer [Hienokuormitusjrjestelm • [88] piirtoon Geneettisten algoritmien soveltaminen suuntaamattomien verkkojen • [Applying GAs to drawing undirected graphs] [207] pika Butterfly oviposition behavior, • biogeography, and lentiviral seuence evol. [281] Pine An Adaptive Computer Vision Technique for Estimating the Biomass and Density of Loblolly • Plantations using Digital Orthophotography and LiDAR Imagery [265] – Multivariate NIR Studies of Seed-Water Interaction in Scots • Seeds (Pinus sylvestris L.) [265] Pinus sylvestris L. Multivariate NIR Studies of SeedWater Interaction in Scots Pine Seeds • [158] pipe GAs in layout sel. for tree-like • networks [499] pipeline Computer-aided gas • operation using GAs and rule learning [413] Placement Alg. Heuristiques et Evol. nistes: Appl. à la R´ esolution du Probl´ eme de • de Formes Irr´ eguli` eres [278] – Finite element analysis and GA opt. design for the actuator • on a large adaptive structure [334] – GAs for partitioning, • and layer assignment for multichip modules [206] – Piezoceramic actuator • for acoustic cntr. of panels [403] planets GAs, pulsar • and ionized interstellar microturbulence [123] planification Alg. génétiques parallèles pour la • de trajectoires de robots en environnement dynamique [360] Planning Automated Electric Distribution Syst. • Using Intelligent Methods and Geographic Info System [77] – Berth allocation • using GAs [445] – Evol. Appr. to Robot Path • [302] – Gen. and geometric opt. of three-dimensional radiation therapy treatment • [81]

51

– –

Kinematic motion • for redundant robots using GAs The Ariadne’s clew alg. : A general • technique, Appl. to automatic path • [537] plans Convergence properties of a class of probabilistic schemes called reproductive • [281] Plantations An Adaptive Computer Vision Technique for Estimating the Biomass and Density of Loblolly Pine • using Digital Orthophotography and LiDAR Imagery [203] plasma Spectroscopic modeling and analysis of • conditions in implosion cores [407] plastic Chemometrics in spectroscopic near infrared imaging for • material recognition [486] – Opt. balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical shells in reinforced concrete including elastic and • material behaviour] [486] plastischem Opt. balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und • Werkstoffverhalten [Opt. of beamlike cylindrical shells in reinforced concrete including elastic and plastic material behaviour] [285] plate Piezoelectric actuator design opt. for shape cntr. of smart composite • structures [392] platelet-derived Determination of 3D structure of suramin in solution and model of interaction of suramin with basic fibroblast and • growth factors [27] Plucked Parameter Estimation of a • String Synthesis Model via the GA [578] populationsgenetischer Evol. und Opt. : Ein • Zugang zu kombinatorischen Optimierungsproblemen [342] point Coupler • path synthesis using a hybrid GA [199] – Near-opt. triangulation of a • set using GAs [234] pole-zero Efficient model fitting using a GA: • approximations of HRTFs [114] policy GAs and cache replacement • [398] Polynomial Advances in • Predictive Filtering: Theory, Design, and Appl. [214] • predictive filters: Impl. and Appl. [363] – Search, • complexity, and the fast messy GAs [501] Population GAs and • Structures — A Massively Par. Alg. [141] – GAs and • structures. A massively par. alg. [195] population-based Gen. local search: A • search alg. [559] populations Simulation of gen. • with biochemical properties [11] potential On finding opt. • customers from a large marketing database – A GA appr. [325] power A GA appr. to sch. resources for a space • syst. [124] – An appl. of GAs to the economic dispatch of • generation [429] – Evol. Strategies for the High-Level Synthesis of VLSIBased DSP Syst. for Low • [16] – Loistehon säätömodulin kehittäminen [Developing of the Reactive • Cntr. ] [504] power plant Nuclear • fault diagnostics and thermal perf. studies using neural networks and GAs [321] pr´ ediction Développement de méthodes besées sur les math´ ematiques, l’informatique et l’intelligence artificielle pour l’alignement de s´ equences et la • de structures prot´ eines [Development of mathematical, computing and artificial intelligence methods for the protein secondary structure prediction] [521] predefined Part sel. for • configurations using gen. search based alg. [571] predictability Long-range • of high-dimensional chaotic dynamics [47] Predicting protein structure using GAs [23] prediction A multiobjective appr. appl. to the protein structure • problem [41] – A Review of AI techniques Appl. to Protein Structure • [321] – Développement de méthodes besées sur les math´ ematiques, l’informatique et l’intelligence artificielle pour l’alignement de s´ equences et la pr´ ediction de structures prot´ eines [Development of mathematical, computing and artificial intelligence methods for the protein secondary structure • [260] – Etude sur la generation de modeles de structures secondaires pour la • de structures proteiques [23] – GA appr. to protein structure • with secondary structures [541] – Global Opt. for Articulated Figures: Molecular Structure • and Motion Synthesis for Animation [525] [294]

52


[355] – An evol. • appr. to probabilistic model-based fault – The appl. of the GA to protein tertiary structure • diagnosis of chemical processes predictions Quantitative-structure based • of displacer and protein affinities in chromatographic syst. [93] Project A Study on the Use of GAs in • Time Sheduling [Tutkimus geneettisten algoritmien kytst projektin aikataulu[398] Predictive Advances in Polynomial • Filtering: The-

[532] [222]

ory, Design, and Appl. – Ennakoivaan simulointiin perustuva panostuotannon optimointi [Batch production opt. by evol. computation and • simulation] [214] – Polynomial • filters: Impl. and Appl. [32] Prescriptive Searching for • Treatment Schedules with a GA: A tool for Forest Management [204] preterm Exploratory data analysis to detect • risk factors [560] primitive A consensus to • extraction [441] Printed Circuit Board Operational and Tactical level Opt. in • Assembly [355] probabilistic An EP appr. to • model-based fault diagnosis of chemical processes [537] – Convergence properties of a class of • schemes called reproductive plans [75] probabilities Adapting opertor • in GAs [413] Probl´ eme Alg. Heuristiques et Evol. nistes: Appl. à la R´ esolution du • de Placement de Formes Irr´ eguli` eres [418] problemas Algoritmo gen´ etico construtivo na otimiza¸ c˜ ao de • combinatoriais de agrupamentos [557] Probleme Einsatz rechnergest¨ utzter Opt. mittels der ES zur l¨ osung galvanotechnischer • [215] Probleml¨ osung durch Komitees neuronaler Netze [472] problemorientierten Flowshop Scheduling mit Par. en Genetischen Algorithmen – Eine • Analyse genetischer Suchstrategien [102] procedural A • formalism for quantum computing [405] – Hierarchical Learning with • Abstraction Mechanisms [498] procedures Machine learning • for generating image domain feature detectors [185] – On the origin of effective • by means of artificial sel. [91] process A heating • alg. for metal forming by a moving heat source [275] – Adaptation Through Stochastic Evol. Neuron Migration • [361] Process control opt. , and modeling of chemical syst. using GAs and neural networks [295] process planning A manufacturing • model using GAs [430] Process Plant Inherent Safety in • Design - An IndexBased Appr. [487] processes GAs for order dependent • appl. to robot path-planning [253] – Incorporation of environmental, economic and production quality criteria in multiobjective eng. design of chlorine/chlorine dioxide softwood kraft pulp bleaching • [543] – The evol. of learning: Simulating the interaction of adaptive • [412] processing Evol. of structures - Optimization of artificial neural structures for info • [147] – Gen. nat. language • [223] – Quantum Info • and its Linear Optical Impl. [388] – Signal • and image restoration techniques for twodimensional eddy current nondestructive evaluation [573] processus Allocation de • sur les architectures parall` eles ´ a m´ emoire distribu´ ee [33] Product A Design Tool Architecture for the Rapid Evaluation of • Design Tradeoffs in an Internet-based Syst. Modeling Environment [17] production Ennakoivaan simulointiin perustuva panostuotannon optimointi [Batch • opt. by evol. computation and predictive simulation] [172] – GAs and neural networks for opt. of hydro power • [253] – Incorporation of environmental, economic and • quality criteria in multiobjective eng. design of chlorine/chlorine dioxide softwood kraft pulp bleaching processes [436] Programa¸ c˜ ao Genética + Algoritmo Genético = CONTROLE GENETICO [Gen. Prog. + GA = Genetic Cntr. ] [21] – Sele¸cão e Avalia¸cãa de Dados de Teste Baseadas em • Gen´ etica [82] Programmieren Ein Kern f¨ ur genetisches • in C++ [Gen. prog. kernel in C++] [193] Programmierung Verbesserung des Simulated Annealing unter Anwendung Genetischer • am Beispiel des Diskreten Quadratischen Layoutproblems [496] programming A study of par. and • in classifier syst. and its appl. to classification in KL-ONE semantic networks [17]

tuksessa] – Risk-based bridge • sel. using GA opt. project planning Decision support for irrigated • using a GA [202] projections Design and opt. of optical diffractive elements using vector space • and pseudo random encoding [267] – Impact des changements globaux sur la biodiversité en Europe : • et incertitudes [93] projektin A Study on the Use of GAs in Project Time Sheduling [Tutkimus geneettisten algoritmien kytst • aikataulutuksessa] [227] propagation Adaptive cntr. of the • of ultrafast light through random and nonlinear media [74] – Par. orbit • and the analysis of satellite constellations [537] properties Convergence • of a class of probabilistic schemes called reproductive plans [559] – Simulation of gen. pop. with biochemical • [321] prot´ eines Développement de méthodes besées sur les math´ ematiques, l’informatique et l’intelligence artificielle pour l’alignement de s´ equences et la pr´ ediction de structures • [Development of mathematical, computing and artificial intelligence methods for the protein secondary structure prediction] [108] protection Using GAs in testing a distribution • relay software — A statistical analysis [23] protein A multiobjective appr. appl. to the • structure prediction problem [41] – A Review of AI techniques Appl. to • Structure Prediction [341] – An evaluation of the GA as a computational tool in • NMR [232] – Computational methods and their appl. for de novo functional • design and membrane • solubilization [321] – Développement de méthodes besées sur les math´ ematiques, l’informatique et l’intelligence artificielle pour l’alignement de s´ equences et la pr´ ediction de structures prot´ eines [Development of mathematical, computing and artificial intelligence methods for the • secondary structure prediction] [23] – GA appr. to • structure prediction with secondary structures [47] – Predicting • structure using GAs [222] – Quantitative-structure based predictions of displacer and • affinities in chromatographic syst. [210] – Simple models of • and small molecule syst. [245] – The appl. of single-pass attenuated total reflectance Fourier transform infrared spectroscopy for • analysis [532] – The appl. of the GA to • tertiary structure prediction [111] Protein folding problem, An Alg. lattice model appr. [70] protein folding problem Appl. of hybridized GAs to the • [246, 272] protein structure A • alignment method and appl. to the discovery of recurrent protein structure motifs [246, 272] protein structure motifs A protein structure alignment method and appl. to the discovery of recurrent • [260] proteiques Etude sur la generation de modeles de structures secondaires pour la prediction de structures • [198] Prozesse Simulation physikalischer und biologischer • zur L¨ osung diskreter Opt. saufgaben [202] pseudo Design and opt. of optical diffractive elements using vector space projections and • random encoding [200] Psychiatric A GA Method for Discovery of Diagnostics Rules for • Disorders [28] puhelinpuheen Neuroevol. Based Artificial Bandwidth Expansion of Telephone Band Speech [Neuroevoluutiopohjainen • taajuuskaistan keinotekoinen laajentaminen] [253] pulp Incorporation of environmental, economic and production quality criteria in multiobjective eng. design of chlorine/chlorine dioxide softwood kraft • bleaching processes [403] pulsar GAs, • planets, and ionized interstellar microturbulence [268] purlins Optimum design of cold-formed steel • using GAs [13] QCL Quantum prog. in • [385] QSAR Appl. of bioinformatics, homology modeling and • to drug design [583] quadratic assignment problem Heuristic and exact alg. for the • [483] [356]


Quadratischen Par. Ansatz zur Lösung des • Zuordnungsproblems [193] – Verbesserung des Simulated Annealing unter Anwendung Genetischer Programmierung am Beispiel des Diskreten • Layoutproblems [377] qualitative Data analysis strategies for • and quantitative determination of organic compounds by Fourier transform infrared spectroscopy (signal processing, pattern recognition, GAs, volatile organic compounds) [584] – GA with • knowledge enchancement for layout design under continuous space formulation [239] Quality Computational Intelligence in Software • Assurance [253] – Incorporation of environmental, economic and production • criteria in multiobjective eng. design of chlorine/chlorine dioxide softwood kraft pulp bleaching processes [377] quantitative Data analysis strategies for qualitative and • determination of organic compounds by Fourier transform infrared spectroscopy (signal processing, pattern recognition, GAs, volatile organic compounds) [358] – Opt. of • variables in discrete event simulation models [222] Quantitative-structure based predictions of displacer and protein affinities in chromatographic syst. [439] Quantization Iterative and Hierarchical Methods for Codebook Generation in Vector • [273] Quantum Cntr. of • Evol. and Josephson Junction circuits [288] – From the Cntr. of • Syst. to Multiqubit Logic [19] – Holonomic • computing [223] • Info Processing and its Linear Optical Impl. [97] – On • Computation [35] – Superconducting Tetrahedral • Bit [282] – Unitary Transformations for • Computing [102] quantum computing A procedural formalism for • [258] – Studies on Boolean functions related to • [13] Quantum programming in QCL [212] quantum systems Using feedback for coherent cntr. of • [302] radiation therapy Gen. and geometric opt. of threedimensional • treatment planning [121] radiophysics Evol. simulation method for automation of • researches [22] rajoitettu VALMA-annoslaskentamallin • optimointi geneettisell¨ a algoritmilla [Constrained Opt. of the VALMA Dose Assessment Model by a GA] [351] Ranch The Hereford • alg. : An improvement of GAs using selective breeding [227] random Adaptive cntr. of the propagation of ultrafast light through • and nonlinear media [318] – Analysis of GAs from a global • search method perspective with techniques for Alg. improvement [202] – Design and opt. of optical diffractive elements using vector space projections and pseudo • encoding [179] randomly Using multiple searches to locate a • moving target [60] range A GA appr. to automating satellite • sch. [444] ranges Guided-mode resonance reflection and transmission filters in the optical and microwave spectral • [352] ranking Contingency • for voltage stability using a GA [554] rapidly Considerations for • converging GAs designed for appl. to problems with expensive evaluation functions [110] Rasterointimenetelm¨ an kehittäminen mustesuihkutulostimelle geneettisell¨ a algoritmilla [49] ratkaiseminen Suurten optimointitehtävien • [Solving large opt. problems] [242] reactions Studies in appl. computational chemistry: META model of photochemical • under UV under nat. conditions and an MCASE appr. to the search of a cure for Parkinson’s disease [16] Reactive Loistehon säätömodulin kehittäminen [Developing of the • Power Cntr. ] [300] real Opt. of FIR digital filters using a • parameter par. GA and impl. s [310] real-time Alg. for comb. opt. in • and their automated refinements by gen. -based learning [137] – GAs for the development of • multi-heuristic search strategies [218] – Measuring evol. testability of • software [424] Real-Time Selecting a Topology for Safety-Critical • Cntr. Syst. [468]

53

real-valued New methods in gen. search with • chromosomes [417] – The structural opt. of atomic and molecular microclusters using a GA in • space-fixed coordinates [557] rechnergest¨ utzter Einsatz • Opt. mittels der ES zur l¨ osung galvanotechnischer Probleme [151] Rechnernetzwerkes Auslegung eines • mit minimalem Kommunikationsaufwand mittels evol. ¨ arer Algorithmen [407] recognition Chemometrics in spectroscopic near infrared imaging for plastic material • [420] – Computational biology: Methods in automated molecular docking with appl. in industrial virology and antibodyantigen • [270] – Feature synthesis and analysis by evol. computation for object detection and • [69] – Myoelectric signal • using gen. prog. [512] – Neural network and gen. learning alg. for computeraided design and pattern • [303] recombination Heuristic • operators for multidimensional decision problems [336] – Incorporation of knowledge in gen. • [337] • sel. , and the gen. construction of computer prog. [427] – The Role of Mutation and • Evol. Alg. [460] – The time complexity of GAs and the theory of • operators [81] – The • Operator, its Correlation to the Fitness Landscape and Search Perf. [118] Recombinationsoperatoren in Genetischen Algorithmen [307] reconfigurable Theory and appl. of modular • robotic syst. [37] Reconfiguration Multi-objective • of Medium Voltage Distribution Networks [Keskij¨ anniteverkkojen kytkent¨ atilanteen monitavoitteinen jakorajaoptimointi] [246, 272] recurrent A protein structure alignment method and appl. to the discovery of • protein structure motifs [73] – Applying GAs to • neural networks for learning network parameters and architecture [298] reducing Techniques for • the disruption of superior building blocks in GAs [525] redundant Kinematic motion planning for • robots using GAs [310] refinements Alg. for comb. opt. in real-time and their automated • by gen. -based learning [245] reflectance The appl. of single-pass attenuated total • Fourier transform infrared spectroscopy for protein analysis [444] reflection Guided-mode resonance • and transmission filters in the optical and microwave spectral ranges [292] Reflectivity Novel Gen. Fitting Alg. and Statistical Error Analysis Method for X-ray • Analysis [457] REGAR Machine learning with rule extraction by gen. assisted reinforcement • Appl. to nonlinear cntr. [469] Regenerierung Kontinuierliche • von ATP f¨ ur enzymatische Synthesen [447] regional Interpretation, modeling and forecasting runoff of • hydrogeologic syst. [291] Registration A Novel Automated Appr. of MultiModality Retinal Image • and Fusion [34] – Multi reslution dental image • based on GAs [400] reglas Aprendizaje de • difusas usando algoritmos gen´ eticos [Concept Learning trought GAs] [264] regularization Novel mutation operators and their appl. to • of artificial neural networks [381] Regulation Universal Service: Issues on Modelling and • [456] Reihenfolgeprobleme Optimieren mit ESn: • nichtlineare und ganzzahlige Opt. [486] reinforced Opt. balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical shells in • concrete including elastic and plastic material behaviour] [457] reinforcement Machine learning with rule extraction by gen. assisted • REGAR: Appl. to nonlinear cntr. [317] Rekombinationsoperatoren f¨ır ESren [508] Rekonstruktion Ein wissensbasierter genetischer Algorithmus zur • physicalischer Ereignisse [492] Relapse from tobacco smoking cessation: Mathematical and computer micro-simulation modelling including parameter opt. with GAs [79]

54

[258]


related

Studies on Boolean functions • to quantum

[494]

relay Using GAs in testing a distribution protection • software — A statistical analysis [263] reliability-based Issues of computational efficiency in • structural opt. [330] Remapping hyperspace and subpartition sampling in iterative gen. search [527] remediation Opt. groundwater • using artificial neural networks and the GA [53] Rendering Approximation der • Equation durch Evol. are Alg. en [415] repairing A chromosome • GA (CRGA) capable of finding exact solution [114] replacement GAs and cache • policy [555] representation Two-dimensional and threedimensional model-based matching using a minimum • criterion and a hybrid GA [537] reproductive Convergence properties of a class of probabilistic schemes called • plans [284] Reprogrammability Appl. of • in Alg. Acceleration [255] requirements Functional • to shape generation in CAD [475] rer ESn zur numerischen Lösung von Adaptationsaufgaben (Dr. • nat.) [343] research A comparison of GAs and other machine learning syst. on a complex classification task from common disease • [121] researches Evol. simulation method for automation of radiophysics • [387] reservoir Opt. hydrocarbon field development using a GA based appr. • [539] resolution GAs and their appl. to problem • and to syst. cntr. [444] resonance Guided-mode • reflection and transmission filters in the optical and microwave spectral ranges [325] resources A GA appr. to sch. • for a space power syst. [248] Response surface methods for experiments involving correlated noise variables [388] restoration Signal processing and image • techniques for two-dimensional eddy current nondestructive evaluation [291] Retinal A Novel Automated Appr. of Multi-Modality • Image Registration and Fusion [41] Review A • of AI techniques Appl. to Protein Structure Prediction [14] – Geneesys – katsaus kolmiulotteiseen keinoelämään nyt ja hahmotelma tulevaisuudesta [A • of 3D AL and Outline of its Future] [546] revolution Drag minimization on a body of • [45] RF Ottimizzazione di cavitá • per acceleratori di particelle [205] Rigorous analysis and design of diffractive optical elements [204] risk factors Exploratory data analysis to detect preterm • [483] Risk-based bridge project sel. using GA opt. [454] RNA A GA for non-enzymic template-directed ligation of • oligomers [230] Robot Automatic and Evol. • Cntr. [445] – Evol. Appr. to • Path Planning [487] – GAs for order dependent processes appl. to • pathplanning [307] robotic Theory and appl. of modular reconfigurable • syst. [123] robots Alg. génétiques parallèles pour la planification de trajectoires de • en environnement dynamique [315] – Estudio de la coordinación inteligente en • b´ıpedos: aplicaci´ on de l´ ogica borrosa y algoritmos gen´ eticos [525] – Kinematic motion planning for redundant • using GAs [229] Robust and Flexible Sch. with Evol. Computation [384] • Sensor Fusion Alg. : Calibration and Cost Minimization [157] Rohrkr¨ ummers Evol. eines • [427] Role The • of Mutation and Recombination Evol. Alg. [345] rotorcraft Using GAs as an automated methodology for conceptual design of • [15] Routing Alg. Library for Large Scale Vehicle • [476] – GA based machine learning appl. to the dynamic • of discrete parts [169] – GAs appl. to a mission • problem [478] – Gen. search and time constrained • [108]

–

Genroute: A hybrid appr. for single and multiple de-

pot •

computing

– Xroute: A knowledge-based • syst. using neural networks and GAs [499] rule Computer-aided gas pipeline operation using GAs and • learning [457] – Machine learning with • extraction by gen. assisted reinforcement REGAR: Appl. to nonlinear cntr. [96] – Parameter Evaluation and Gen. -Based • Learning for the Differential Diagnosis of Female Urinary Incontinence [297] rule-based Gen. design of • fuzzy cntr. [200] Rules A GA Method for Discovery of Diagnostics • for Psychiatric Disorders [558] – Empirical studies of default hierarchies and sequences of • in learning classifier syst. [517] – Inductive learning of decision • from attribute-based examples: A knowledge-intensive GA appr. [254] – News and Trading • [309] – Using GAs to find technical trading • in financial markets [447] runoff Interpretation, modeling and forecasting • of regional hydrogeologic syst. [430] Safety Inherent • in Process Plant Design - An IndexBased Appr. [219] Safety-Critical A Search-Based Automated Test-Data Generation Framework for • Software [424] – Selecting a Topology for • Real-Time Cntr. Syst. [330] sampling Remapping hyperspace and subpartition • in iterative gen. search [60] satellite A GA appr. to automating • range sch. [74] – Par. orbit propagation and the analysis of • constellations [473] satisfiability GAs and the • of large-scale Boolean expressions [505] Saugkopfeinl¨ aufen Opt. von • zur gewinnung mariner lockermaterialien mit hilfe der evol. sstrategischen Experimentiertechnik [15] Scale Alg. Library for Large • Vehicle Routing [286] Scales Evaluating the Spatial Ecology of Anthrax in North America: Examining Epidemiological Components Across Multiple Geographic • Using a GIS-Based Appr. [322] scheduler Gen. -neuro • [32] Schedules Searching for Prescriptive Treatment • with a GA: A tool for Forest Management [109] scheduling A finite capacity • syst. for a silicon wafer manufacturer [Hienokuormitusjrjestelm piikiekkovalmistajalle] [60] – A GA appr. to automating satellite range • [325] – A GA appr. to • resources for a space power syst. [122] – Dynamic • of computer tasks using GAs [472] Scheduling Flowshop • mit Par. en Genetischen Algorithmen – Eine problemorientierten Analyse genetischer Suchstrategien [402] Scheduling GA-Based • Syst. for Dynamic Job-Shop Sch. Problems [481] – GAs and neural networks appl. to manufacturing • [467] – Instruction • using GAs [133] – Investigating GAs for • [164] – Optimising flowshop • through adaptive GAs [390] – Opt. of seasonal irrigation • by GAs (adaptive penalty) [192] – Par. GAs for Single Machine Job • with Earliness and Tardiness Penalties [229] – Robust and Flexible • with Evol. Computation [386] Scheduling Theory On Merging Sequencing and • with GAs to Solve Stochastic Job Shops [537] schemes Convergence properties of a class of probabilistic • called reproductive plans [359] – High quality tour hybrid gen. • for TSP opt. problems [197] Schrittweitensteuerung Theoretische Betrachtungen zur • in ESn [140] Schwebewaage Simulation einer unterschaligen • auf einem Analogrechner und Opt. ihres einsschwingverhaltens mit der ES [509] Schwingungsanalyse Der Einsatz eines Mikrorechners zur hybriden Opt. und • [265] Scots Multivariate NIR Studies of Seed-Water Interaction in • Pine Seeds (Pinus sylvestris L.) [138] Search Adaptive Syst. and the • for Opt. Index Sel. [482] – Adaptive • using simulated evol. [174] – An investigation of diploid GAs for adaptive • on nonstationary functions [389] – Coevol. • among Adversaries [522]


– Cntr. partitioning opt. for STOVL aircraft using gen. • methods [526] – Enhanced GAs in constrained • spaces with emphasis in par. environments [370] – Evol. Alg. , Fitness Landscapes and • [552] – Evol. structure and • [485] – Experimentation with an adaptive • strategy for solving a key-board design/configuring problem [137] – GAs for the development of real-time multi-heuristic • strategies [195] – Gen. local search: A pop. -based • alg. [478] – Gen. • and time constrained routing [479] – Gen. • methods for multicriterion opt. design of viscoelastically damped structures [221] – Local • and Variable Neighborhood • Alg. for the Vehicle Routing Problem with Time Windows [79] – New methods in gen. • with real-valued chromosomes [363] • polynomial complexity, and the fast messy GAs [497] – Non-linearities in gen. adaptive • [409] – Opt. with evol. alg. and local • [521] – Part sel. for predefined configurations using gen. • based alg. [330] – Remapping hyperspace and subpartition sampling in iterative gen. • [242] – Studies in appl. computational chemistry: META model of photochemical reactions under UV under nat. conditions and an MCASE appr. to the • of a cure for Parkinson’s disease [81] – The Recombination Operator, its Correlation to the Fitness Landscape and • Perf. [340] – Towards opt. circuit layout using advanced • techniques [318] search method Analysis of GAs from a global random • perspective with techniques for Alg. improvement [159] search space A technique for • adaption with simulated annealing & GAs in image registration [219] Search-Based A • Automated Test-Data Generation Framework for Safety-Critical Software [29] search-based Evol. computing in • software eng. [179] searches Using multiple • to locate a randomly moving target [299] searching GANNet: A GA for • topology and weight spaces in neural network design. The first step in finding neural network solution [434] • for chemical reaction mechanisms with GAs [32] • for Prescriptive Treatment Schedules with a GA: A tool for Forest Management [390] seasonal Opt. of • irrigation sch. by GAs (adaptive penalty) [260] secondaires Etude sur la generation de modeles de structures • pour la prediction de structures proteiques [23] secondary GA appr. to protein structure prediction with • structures [321] secondary structure Développement de méthodes bes´ ees sur les math´ ematiques, l’informatique et l’intelligence artificielle pour l’alignement de s´ equences et la pr´ ediction de structures prot´ eines [Development of mathematical, computing and artificial intelligence methods for the protein • prediction] [265] Seeds Multivariate NIR Studies of Seed-Water Interaction in Scots Pine • (Pinus sylvestris L.) [265] Seed-Water Multivariate NIR Studies of • Interaction in Scots Pine Seeds (Pinus sylvestris L.) [572] segmentation Automated image • and interpretation using GAs and semantic nets [65] Selbstanpassung Lokale • von Parametern massiv par. er genetischer Alg. en [21] Sele¸ c˜ ao e Avalia¸cãa de Dados de Teste Baseadas em Prog. a¸ c˜ ao Gen´ etica [424] Selecting a Topology for Safety-Critical Real-Time Cntr. Syst. [581] selection A stochastic generalization of Eigen’s model of nat. • [138] – Adaptive Syst. and the Search for Opt. Index • [116] – Adaptive • methods for cntr. convergence in GAs [465] – An analysis of the effects of • in GAs [480] – Component • opt. using GAs [120] – GAs for feature • [158] – GAs in layout • for tree-like pipe networks [185] – On the origin of effective procedures by means of artificial • [63]

55

– Part • for predefined configurations using gen. search based alg. [337] – Recombination, • and the gen. construction of computer prog. [483] – Risk-based bridge project • using GA opt. [351] selective The Hereford Ranch alg. : An improvement of GAs using • breeding [181] self-referential Evol. principles in • learning, or on learning how to learn: the meta-meta-...hook [496] semantic A study of par. and prog. in classifier syst. and its appl. to classification in KL-ONE • networks [572] – Automated image segmentation and interpretation using GAs and • nets [261] semiconductor Modeling and decision-making in a • supply chain [384] Sensor Fusion Robust • Alg. : Calibration and Cost Minimization [426] sensors Computational methods for the opt. of the mapping of actuators and • in the cntr. of flexible structures [375] Sentinel Evol. -Assisted Discovery of • Features in Epidemiologic Surveillance [558] sequences Empirical studies of default hierarchies and • of rules in learning classifier syst. [386] Sequencing On Merging • and Sch. Theory with GAs to Solve Stochastic Job Shops [569] – Opt. of • problems using GAs [256] – Par. hierarchical adaptive GA for genome • [348] sequential Discrete opt. of structures under dynamic loading by using • and par. evol. strategies [66] – Evolving • neural networks for time series forecasting [391] – Symbiotic Evol. of Neural Networks in • Decision Tasks [381] Service Universal • Issues on Modelling and Regulation [199] set Near-opt. triangulation of a point • using GAs [71] set covering problem Evol. divide and conquer for the • [312] set partitioning problem A par. GA for the • [207] seuence Butterfly oviposition behavior, pika biogeography, and lentiviral • evol. [217] shallow Broadband nonlinear inversion for geoacoustic parameters in • water [440] shape Cam • opt. by GA [95] – Diesel-moottorin nokka-akselin muodon optimointi geneettisell¨ a algoritmilla [Diesel engine cam • design by GA] [255] – Functional requirements to • generation in CAD [382] – Impl. and Alg. of a Tree • Par. Computer [285] – Piezoelectric actuator design opt. for • cntr. of smart composite plate structures [374] – Use of GAs in • opt. [354] Shape Optimization Zeroth-Order • Utilizing a Learning Classifier Syst. [93] Sheduling A Study on the Use of GAs in Project Time • [Tutkimus geneettisten algoritmien kytst projektin aikataulutuksessa] [289] sheet metal forming process Design for uncertainties of • [486] shells Opt. balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical • in reinforced concrete including elastic and plastic material behaviour] [500] shifts Adaptive behavior of simulated bacterial cells subjected to nutritional • [69] signal Myoelectric • recognition using gen. prog. [388] • processing and image restoration techniques for twodimensional eddy current nondestructive evaluation [377] signal processing Data analysis strategies for qualitative and quantitative determination of organic compounds by Fourier transform infrared spectroscopy • pattern recognition, GAs, volatile organic compounds) [419] – Opt. of • and network cntr. in telecommunications syst. [220] signals A dynamical model of the distr. interaction of intracellular • [109] silicon A finite capacity sch. syst. for a • wafer manufacturer [Hienokuormitusjrjestelm piikiekkovalmistajalle] [83] SIMD Machine FEM Mesh Mapping to a • Using GAs [372] simplex Modeling of metabolic syst. using fuzzy logic and supervisory • GA (enzyme kinetics, Escherichia coli, glycolysis, tricarboxylic acid cycle) [500] simulated Adaptive behavior of • bacterial cells subjected to nutritional shifts [482] – Adaptive search using • evol. [521]

56


[108] – Using GAs in testing a distribution protection relay • – Syst. Ident. through • Evol. — A statistical analysis simulated annealing A technique for search space adaption with • & GAs in image registration [107] software testing Automaattinen ohjelmien testaus optimoimalla geneettisill¨ a algoritmeilla [Automatic • by opt. [502] • und ES: Ein vergleich anhand schweriger Opt. sprob[135] [159]

with GAs]

leme

–

The design, analysis, and impl. of par. • and parallel GAs for the composite graph coloring problem [570] – Towards an extrapolation of the • convergence theory onto the simple GA [193] Simulated Annealing Verbesserung des • unter Anwendung Genetischer Programmierung am Beispiel des Diskreten Quadratischen Layoutproblems [543] Simulating The evol. of learning: • the interaction of adaptive processes [462] simulation A multi-objective • opt. method using a GA with appl. in manufacturing [238] – Aspects of modelling and • of GAs: a formal appr. [580] – Computer • of a living cell [503] – Computer • of gen. adaptation: Par. subcomponent interaction in a multilocus model [506] Simulation Ein Vergleich von Opt. sverfahren f¨ ur die zeitdiskrete • [17] simulation Ennakoivaan simulointiin perustuva panostuotannon optimointi [Batch production opt. by evol. computation and predictive • [121] – Evol. • method for automation of radiophysics researches [140] • einer unterschaligen Schwebewaage auf einem Analogrechner und Opt. ihres einsschwingverhaltens mit der ES [547] • of a cell-assembly model [396] • of condensed-phase physical, chemical, and biological syst. on massively par. computers (free energy perturbation, MIMD,malate dehydrogenase, enzymes, GA) [559] • of gen. pop. with biochemical properties [198] • physikalischer und biologischer Prozesse zur L¨ osung diskreter Opt. saufgaben [358] – Opt. of quantitative variables in discrete event • models [585] – The opt. of • models by GAs: A comparative study [514] – Tolerance opt. using GA and approximated • [332] simulation-based Hierarchical, asynchronous par. GAs for • syst. design [349] Simulierte MathEvolvica – • Evol. von Entwicklungsprog. men der Natur [17] simulointiin Ennakoivaan • perustuva panostuotannon optimointi [Batch production opt. by evol. computation and predictive simulation] [192] Single Par. GAs for • Machine Job Sch. with Earliness and Tardiness Penalties [494] – Genroute: A hybrid appr. for • and multiple depot routing [245] single-pass The appl. of • attenuated total reflectance Fourier transform infrared spectroscopy for protein analysis [99] sis¨ aiset Geneettisten algoritmien käyttö tutkittaessa sumean logiikan hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a taajuusmuuttajan • s¨ a¨ at¨ aj¨ at [Evaluating the benefit of fuzzy logic for PID-cntr. by means of GAs - case: frequency cntr. ] [30] skill Taitoa vaativien tehtävien oppiminen ja suoritus WorkPartner-robotilla [Learning and performing • demanding tasks with WorkPartner robot] [252] SLS machine Strategies of distr. GAs for threedimensional bin packing in a • [285] smart Piezoelectric actuator design opt. for shape cntr. of • composite plate structures [103] Soft Applying • Computing in Manufacturing [Pehmolaskennan soveltaminen tehdasymp¨ arist¨ oss¨ a] [314] soft computing Automatic design and adaptation of fuzzy syst. and GAs using • techniques [451] Soft Computing Methods for Cntr. and Instrumentation [89] Software A Description, Analysis, and Comparison of a Hardware and • Impl. of the SPLASH GA for opt. symmetric traveling salesman problems [150] – A methodology for • cost estimation using machine learning techniques [219] – A Search-Based Automated Test-Data Generation Framework for Safety-Critical • [239] – Computational Intelligence in • Quality Assurance [29] – Evol. computing in search-based • eng. [218] – Measuring evol. testability of real-time • [378] – The Automatic Generation of • Test Data using GAs [493]

[257] [253]

Software Testing Automatic • by GAs softwood Incorporation of environmental, economic

and production quality criteria in multiobjective eng. design of chlorine/chlorine dioxide • kraft pulp bleaching processes [383] Solid Generic Evol. Design of • Objects using a GA [232] solubilization Computational methods and their appl. for de novo functional protein design and membrane protein • [415] solution A chromosome repairing GA (CRGA) capable of finding exact • [12] – Computation of Incentive Stackelberg • [Stackelbergin pelin kannusteratkaisun laskeminen] [392] – Determination of 3D structure of suramin in • and model of interaction of suramin with basic fibroblast and platelet-derived growth factors [299] – GANNet: A GA for searching topology and weight spaces in neural network design. The first step in finding neural network • [208] – On • Appr. for Some Industrially Motivated Comb. Opt. Problems [84] – Sähkön hankinnan optimointi [Economic dispatch problem, a comparison of some • methods] [453] Solutions Alg. for Coevol. of • and Fitness Cases in Asymmetric Problem Domains [64] – GAs and Multiple Distinct • [184] – Manipulating subpop. of feasible and infeasible • in GAs [386] Solve On Merging Sequencing and Sch. Theory with GAs to • Stochastic Job Shops [49] Solving Suurten optimointitehtävien ratkaiseminen • large opt. problems] [103] soveltaminen Applying Soft Computing in Manufacturing [Pehmolaskennan • tehdasymp¨ arist¨ oss¨ a] [42] – Geneettisen algoritmin • moottoroidun hengityksensuojaimen toimintaparametrien optimointiin [88] – Geneettisten algoritmien • suuntaamattomien verkkojen piirtoon [Applying GAs to drawing undirected graphs] [325] space A GA appr. to sch. resources for a • power syst. [202] – Design and opt. of optical diffractive elements using vector • projections and pseudo random encoding [584] – GA with qualitative knowledge enchancement for layout design under continuous • formulation [236] – Studies on the Theory and Design • of Memetic Alg. [368] spacecraft An investigation of the applicability of GAs to • trajectory opt. [417] space-fixed The structural opt. of atomic and molecular microclusters using a GA in real-valued • coordinates [549] Spaces Analysis and Appl. of Darwinian opt. Alg. in the Multidimensional • [526] – Enhanced GAs in constrained search • with emphasis in par. environments [299] – GANNet: A GA for searching topology and weight • in neural network design. The first step in finding neural network solution [191] spanning A GA for the minimum • tree problem [286] Spatial Evaluating the • Ecology of Anthrax in North America: Examining Epidemiological Components Across Multiple Geographic Scales Using a GIS-Based Appr. [544] speciation Experimental study of • in ecological niche theory using GAs [233] Species Innate Intelligence for Artificial Organisms: via • Evol. of Neural Networks [444] spectral Guided-mode resonance reflection and transmission filters in the optical and microwave • ranges [249] spectrometer Data compression alg. for the geosynchronous imaging Fourier transform • [407] spectroscopic Chemometrics in • near infrared imaging for plastic material recognition [203] • modeling and analysis of plasma conditions in implosion cores [377] spectroscopy Data analysis strategies for qualitative and quantitative determination of organic compounds by Fourier transform infrared • (signal processing, pattern recognition, GAs, volatile organic compounds) [201] – Femtosecond time-resolved photoelectron • of phenol [228] – Infrared • in clinical chemistry, using chemometric calibration techniques


Speech Neuroevol. Based Artificial Bandwidth Expansion of Telephone Band • [Neuroevoluutiopohjainen puhelinpuheen taajuuskaistan keinotekoinen laajentaminen] [89] SPLASH A Description, Analysis, and Comparison of a Hardware and Software Impl. of the • GA for opt. symmetric traveling salesman problems [162] splitting Par. GA for the DAG vertex • problem [352] stability Contingency ranking for voltage • using a GA [244] stabilized A • finite element formulation for the opt. design of forming processes [12] Stackelberg Computation of Incentive • Solution [Stackelbergin pelin kannusteratkaisun laskeminen] [12] Stackelbergin Computation of Incentive Stackelberg Solution • pelin kannusteratkaisun laskeminen] [486] Stahlbeton Opt. balkenartiger Zylinderschalen aus • mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical shells in reinforced concrete including elastic and plastic material behaviour] [448] Standard Cell Placement A GA for Mixed Macro and • that Directly Incorporates Cell Membership Info [127] Standortplanung Kombinierte Touren- und • bei der Hausm¨ ullentsorgung mit einem evol. sstrategischen Ansatz [471] station¨ arer Ein Evolutionsverfahren zur mathematischen Modellierung • Zust¨ ande in dynamischen Systemen [85] statistical Hissien ohjausjärjestelmien tilastollinen vertailu [A • comparison of two elevator call allocation method] [438] – Methods for • Inference: Extending the Evol. Computation Paradigm [292] – Novel Gen. Fitting Alg. and • Error Analysis Method for X-ray Reflectivity Analysis [108] – Using GAs in testing a distribution protection relay software — A • analysis [266] statistics Evol. alg. for • and finance [268] steel Optimum design of cold-formed • purlins using GAs [235] Steel Beam Structures Automated Formulation of Opt. models for • [149] Steiner tree The directed • problem: An appl. of GAs [299] step GANNet: A GA for searching topology and weight spaces in neural network design. The first • in finding neural network solution [581] stochastic A • generalization of Eigen’s model of nat. sel. [275] – Adaptation Through • Evol. Neuron Migration Process [404] – Learning gene linkage to effectively solve problems of bounded difficulty using GAs (problem solving, • opt. ) [458] • iterated gen. hillclimbing [386] – On Merging Sequencing and Sch. Theory with GAs to Solve • Job Shops [531] Stochastische Automatische Bemessung f¨ ur • Dynamische Belastung [306] stock cutting An appr. to three-dimensional • using GAs [63] STOVL Cntr. partitioning opt. for • aircraft using gen. search methods [167] Str¨ omungsexperiments Automatisierung eines evol. sstrategischen • [183] Str¨ omungstechnik Kynernetische Evolution als Strategie der experimellen Forschung in der • [183] Strategie Kynernetische Evolution als • der experimellen Forschung in der Str¨ omungstechnik [144] Strategien Chip-Assembly • bei der Layout-Synthese nach Floorplan-Vorgaben [507] strategies Coding • for GAs and neural nets [377] – Data analysis • for qualitative and quantitative determination of organic compounds by Fourier transform infrared spectroscopy (signal processing, pattern recognition, GAs, volatile organic compounds) [538] – Delta coding • for GAs [137] – GAs for the development of real-time multi-heuristic search • [252] • of distr. GAs for three-dimensional bin packing in a SLS machine [485] strategy Experimentation with an adaptive search • for solving a key-board design/configuring problem [27] String Parameter Estimation of a Plucked • Synthesis Model via the GA [168] strings Walsh function analysis of GAs of nonbinary • [263] structural Issues of computational efficiency in reliability-based • opt. [28]

57

– •

Multicriteria • opt. by GA opt. of cage induction motors using finite element analysis [57] • opt. of feedforward neural networks using GA [376] • opt. of induction motor using GA and finite element method [224] • studies of the human DNA repair protein oxygen-6alkylguanine-DNA alkyltransferase [209] – The evol. • opt. (ESO) method: Theoretical aspects and the modified evol. ary • optimization (MESO) method [417] – The • opt. of atomic and molecular microclusters using a GA in real-valued space-fixed coordinates [518] – Topological • design using GAs [23] structure A multiobjective appr. appl. to the protein • prediction problem [41] – A Review of AI techniques Appl. to Protein • Prediction [552] – Evol. • and search [278] – Finite element analysis and GA opt. design for the actuator placement on a large adaptive • [23] – GA appr. to protein • prediction with secondary structures [541] – Global Opt. for Articulated Figures: Molecular • Prediction and Motion Synthesis for Animation [94] – Learning the • of neural networks using GAs [44] – Local • opt. in evol. generated neural network architectures [296] • determination alg. in computational X-ray crystallography [47] – Predicting protein • using GAs [394] structure-based The design of a ligand discovery and opt. syst. for • drug design [426] structures Computational methods for the opt. of the mapping of actuators and sensors in the cntr. of flexible • [338] – Computer-assisted drug design: GAs and • of molecular clusters of aromatic hydrocarbons and actinomycin Ddeoxyguanosine [259] – Decomposition-based assembly synthesis of family of • [321] – Développement de méthodes besées sur les math´ ematiques, l’informatique et l’intelligence artificielle pour l’alignement de s´ equences et la pr´ ediction de • prot´ eines [Development of mathematical, computing and artificial intelligence methods for the protein secondary structure prediction] [348] – Discrete opt. of • under dynamic loading by using sequential and par. evol. strategies [260] – Etude sur la generation de modeles de • secondaires pour la prediction de • proteiques [412] – Evol. of • - Optimization of artificial neural • for info processing [23] – GA appr. to protein structure prediction with secondary • [501] – GAs and Pop. • — A Massively Par. Alg. [141] – GAs and pop. • A massively par. alg. [479] – Gen. search methods for multicriterion opt. design of viscoelastically damped • [333] – Opt. de forme des • électromagnétiques [285] – Piezoelectric actuator design opt. for shape cntr. of smart composite plate • [528] – The impact of data • on the perf. of gen. -alg. -based learning [152] Strukturkomponenten Entwicklung von ComputerAlgorithmen zur Opt. von • nach der Evol. stheorie [40] Strukturtests Automatisierung von • mit evol. ären Alg. en [503] subcomponent Computer simulation of gen. adaptation: Par. • interaction in a multilocus model [500] subjected Adaptive behavior of simulated bacterial cells • to nutritional shifts [330] subpartition Remapping hyperspace and • sampling in iterative gen. search [184] subpopulations Manipulating • of feasible and infeasible solutions in GAs [189] Suche Par. isierung Genetischer Algorithmen zur • und Opt. [190] suchstrategien Anwendung evolutorischer • zur topdown-rechnung von budgetierungsmodellen [472] Suchstrategien Flowshop Scheduling mit Par. en Genetischen Algorithmen – Eine problemorientierten Analyse genetischer • [327] [59]

58

sumean logiikan Geneettisten algoritmien käyttö tutkittaessa • hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the benefit of fuzzy logic for PID-cntr. by means of GAs - case: frequency cntr. ] [30] suoritus Taitoa vaativien tehtävien oppiminen ja • WorkPartner-robotilla [Learning and performing skill demanding tasks with WorkPartner robot] [35] Superconducting Tetrahedral Quantum Bit [298] superior Techniques for reducing the disruption of • building blocks in GAs [416] Supervised An Investigation of • Learning in Gen. Prog. [372] supervisory Modeling of metabolic syst. using fuzzy logic and • simplex GA (enzyme kinetics, Escherichia coli, glycolysis, tricarboxylic acid cycle) [261] supply chain Modeling and decision-making in a semiconductor • [392] suramin Determination of 3D structure of • in solution and model of interaction of • with basic fibroblast and plateletderived growth factors [375] Surveillance Evol. -Assisted Discovery of Sentinel Features in Epidemiologic • [88] suuntaamattomien Geneettisten algoritmien soveltaminen • verkkojen piirtoon [Applying GAs to drawing undirected graphs] [101] Suurnopeusoikosulkukoneen optimointi [49] Suurten optimointitehtävien ratkaiseminen [Solving large opt. problems] [391] Symbiotic Evol. of Neural Networks in Sequential Decision Tasks [519] symbolic A hierarchical gen. syst. for • function ident. [89] symmetric A Description, Analysis, and Comparison of a Hardware and Software Impl. of the SPLASH GA for opt. • traveling salesman problems [469] Synthesen Kontinuierliche Regenerierung von ATP f¨ ur enzymatische • [342] synthesis Coupler point path • using a hybrid GA [259] – Decomposition-based assembly • of family of structures [429] – Evol. Strategies for the High-Level • of VLSI-Based DSP Syst. for Low Power [541] – Global Opt. for Articulated Figures: Molecular Structure Prediction and Motion • for Animation [316] – Hybrid GAs with hyperplane • A theoretical and empirical study [329] – Neural network • using cellular encoding and the GA [27] – Parameter Estimation of a Plucked String • Model via the GA [213] syst` eme Implantation d’un • éolien, opt. par alg. g´ en´ etiques [533] Systeme Bionische Verfahren zur Entwicklung visueller • [556] – ES: Opt. technischer • nach Prinzipien der biologischen Evolution [471] Systemen Ein Evolutionsverfahren zur mathematischen Modellierung station¨ arer Zust¨ ande in dynamischen • [28] taajuuskaistan Neuroevol. Based Artificial Bandwidth Expansion of Telephone Band Speech [Neuroevoluutiopohjainen puhelinpuheen • keinotekoinen laajentaminen] [99] taajuusmuuttajan Geneettisten algoritmien käyttö tutkittaessa sumean logiikan hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a • sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the benefit of fuzzy logic for PID-cntr. by means of GAs - case: frequency cntr. ] [441] Tactical Operational and • level Opt. in Printed Circuit Board Assembly [30] Taitoa vaativien tehtävien oppiminen ja suoritus WorkPartner-robotilla [Learning and performing skill demanding tasks with WorkPartner robot] [192] Tardiness Par. GAs for Single Machine Job Sch. with Earliness and • Penalties [179] target Using multiple searches to locate a randomly moving • [343] task A comparison of GAs and other machine learning syst. on a complex classification • from common disease research [474] – Intelligent behavior as an adaptation to the • environment [122] tasks Dynamic sch. of computer • using GAs [391] – Symbiotic Evol. of Neural Networks in Sequential Decision • [99]


– Taitoa vaativien tehtävien oppiminen ja suoritus WorkPartner-robotilla [Learning and performing skill demanding • with WorkPartner robot] [240] Technical Syst. Usability of Complex • Syst. [309] – Using GAs to find • trading rules in financial markets [150] techniques A methodology for software cost estimation using machine learning • [41] – A Review of AI • Appl. to Protein Structure Prediction [318] – Analysis of GAs from a global random search method perspective with • for Alg. improvement [425] – Appl. and limitations of GAs for the opt. of multivariate calibration • [314] – Automatic design and adaptation of fuzzy syst. and GAs using soft computing • [228] – Infrared spectroscopy in clinical chemistry, using chemometric calibration • [388] – Signal processing and image restoration • for twodimensional eddy current nondestructive evaluation [340] – Towards opt. circuit layout using advanced search • [556] technischer ES: Opt. • Systeme nach Prinzipien der biologischen Evolution [134] – Opt. e dimensionierung • konstruktionen [103] tehdasymp¨ arist¨ oss¨ a Applying Soft Computing in Manufacturing [Pehmolaskennan soveltaminen • [30] teht¨ avien Taitoa vaativien • oppiminen ja suoritus WorkPartner-robotilla [Learning and performing skill demanding tasks with WorkPartner robot] [419] telecommunications Opt. of signal processing and network cntr. in • syst. [28] Telephone Neuroevol. Based Artificial Bandwidth Expansion of • Band Speech [Neuroevoluutiopohjainen puhelinpuheen taajuuskaistan keinotekoinen laajentaminen] [454] template-directed A GA for non-enzymic • ligation of RNA oligomers [39] terminals GA opt. of antennas for mobile • [Matkapuhelinantennien optimointi geneettisell¨ a algoritmilla] [532] tertiary structure The appl. of the GA to protein • prediction [36] test A hybrid GA for automatic • data generation [26] – GA based • Data Generation [378] Test Data The Automatic Generation of Software • using GAs [218] testability Measuring evol. • of real-time software [107] testaus Automaattinen ohjelmien • optimoimalla geneettisill¨ a algoritmeilla [Automatic software testing by opt. with GAs] [219] Test-Data A Search-Based Automated • Generation Framework for Safety-Critical Software [21] Teste Sele¸cão e Avalia¸cãa de Dados de • Baseadas em Prog. a¸ c˜ ao Gen´ etica [108] testing Using GAs in • a distribution protection relay software — A statistical analysis [35] Tetrahedral Superconducting • Quantum Bit [304] Thedetermination of invariant parameters and operators of the traditional GA using an adaptive gen. alg. generator [316] theoretical Hybrid GAs with hyperplane synthesis: A • and empirical study [209] Theoretical The evol. structural opt. (ESO) method: • aspects and the modified evol. ary structural optimization (MESO) method [197] Theoretische Betrachtungen zur Schrittweitensteuerung in ESn [566] Theorie Ein beitrag zur • der ES [564] theory A computational • of learning in distr. syst. [398] – Advances in Polynomial Predictive Filtering: • Design, and Appl. [536] – Contributions to the • and Appl. of GAs [335] – Evol. Alg. in • and Practice [544] – Experimental study of speciation in ecological niche • using GAs [251] – Explicit building-block multiobjective GAs: • analysis, and development [307] • and appl. of modular reconfigurable robotic syst. [236] – Studies on the • and Design Space of Memetic Alg. [460] – The time complexity of GAs and the • of recombination operators [570] – Towards an extrapolation of the simulated annealing convergence • onto the simple GA [504] thermal Nuclear power plant fault diagnostics and • perf. studies using neural networks and GAs [30]


[428]

Three-Dimensional

59

A GA for a • Non-Convex Bin

Packing Problem [306]

three-dimensional

An appr. to • stock cutting using

GAs

– Gen. and geometric opt. of • radiation therapy treatment planning [252] – Strategies of distr. GAs for • bin packing in a SLS machine [555] – Two-dimensional and • model-based matching using a minimum Rep. criterion and a hybrid GA [563] tietokannan Induktiivinen oppiminen metsänviljelyn • tulkinnassa [Inductive learning in interpretation of databases of forest cultivation] [85] tilastollinen Hissien ohjausjärjestelmien • vertailu [A statistical comparison of two elevator call allocation method] [93] Time A Study on the Use of GAs in Project • Sheduling [Tutkimus geneettisten algoritmien kytst projektin aikataulutuksessa] [478] – Gen. search and • constrained routing [24] – Opt. GAs for • Critical Problems [575] – Gideon: A GA syst. for vehicle routing with • windows [460] – The • complexity of GAs and the theory of recombination operators [66] time series Evolving sequential neural networks for • forecasting [106] time windows A hybrid GA for the vehicle routing problem with • [221] Time Windows Local Search and Variable Neighborhood Search Alg. for the Vehicle Routing Problem with • [262] time-domain Two-dimensional • inversion of perfect conductors using the GA [201] time-resolved Femtosecond • photoelectron spectroscopy of phenol [56] timetabling GAs for • [90] timing GA in dynamic traffic signal • the CabalBLmodel [492] tobacco smoking Relapse from • cessation: Mathematical and computer micro-simulation modelling including parameter opt. with GAs [42] toimintaparametrien Geneettisen algoritmin soveltaminen moottoroidun hengityksensuojaimen • optimointiin [514] Tolerance opt. using GA and approximated simulation [33] Tool A Design • Architecture for the Rapid Evaluation of Product Design Tradeoffs in an Internet-based Syst. Modeling Environment [341] – An evaluation of the GA as a computational • in protein NMR [46] – Eine Entwicklungsumgebung zum Monitoring Genetischer Algorithmen [A development • for monitoring GAs] [534] – GAs as a computational • for design [32] – Searching for Prescriptive Treatment Schedules with a GA: A • for Forest Management [397] tools The development of new • for homology modeling [577] – Two analysis • to describe the operation of classifier syst. [190] top-down-rechnung Anwendung evolutorischer suchstrategien zur • von budgetierungsmodellen [280] Topological Approximation Alg. for Some • Invariants of Graphs [518] • structural design using GAs [362] topologique Alg. génétiques et Opt. • [299] topology GANNet: A GA for searching • and weight spaces in neural network design. The first step in finding neural network solution [424] – Selecting a • for Safety-Critical Real-Time Cntr. Syst. [323] – The use of GAs to optimise chemical flowshops of unrestricted • [245] total The appl. of single-pass attenuated • reflectance Fourier transform infrared spectroscopy for protein analysis [359] tour High quality • hybrid gen. schemes for TSP opt. problems [127] Touren Kombinierte • und Standortplanung bei der Hausm¨ ullentsorgung mit einem evol. sstrategischen Ansatz [33] Tradeoffs A Design Tool Architecture for the Rapid Evaluation of Product Design • in an Internet-based Syst. Modeling Environment [254] Trading News and • Rules [309] – Using GAs to find technical • rules in financial markets [302]

traditional Thedetermination of invariant parameters and operators of the • GA using an adaptive gen. alg. generator [90] traffic signal GA in dynamic • timing: the CabalBLmodel [435] Training based opt. of nonlinear digital filters: Case studies [123] trajectoires Alg. génétiques parallèles pour la planification de • de robots en environnement dynamique [368] trajectory An investigation of the applicability of GAs to spacecraft • opt. [282] Transformations Unitary • for Quantum Computing [444] transmission Guided-mode resonance reflection and • filters in the optical and microwave spectral ranges [582] transportation Opt. of • network design problems using a cumulative GA and neural networks [182] Transputersystemen Untersuchungen zur Effizienz mehrgliedriger asynchroner ESn auf • [568] traveling salesman problem A GA for the • [89] traveling salesman problems A Description, Analysis, and Comparison of a Hardware and Software Impl. of the SPLASH GA for opt. symmetric • [166] Travelling Salesman Problems Ein par. er Evolutionsalg. us zur L¨ osung des • [274] T-ray Three Dimensional • Inspection Syst. [302] treatment Gen. and geometric opt. of threedimensional radiation therapy • planning [32] – Searching for Prescriptive • Schedules with a GA: A tool for Forest Management [191] tree A GA for the minimum spanning • problem [382] – Impl. and Alg. of a • Shape Par. Computer [158] tree-like GAs in layout sel. for • pipe networks [199] triangulation Near-opt. • of a point set using GAs [372] tricarboxylic Modeling of metabolic syst. using fuzzy logic and supervisory simplex GA (enzyme kinetics, Escherichia coli, glycolysis, • acid cycle) [400] trought Aprendizaje de reglas difusas usando algoritmos gen´ eticos [Concept Learning • GAs] [78] Trusted Study of Covert Channels in a • Unix Syst. [311] TSP An empirical computational study of GAs to solve order based problems: An emphasis on • and VRPTC [359] – High quality tour hybrid gen. schemes for • opt. problems [14] tulevaisuudesta Geneesys – katsaus kolmiulotteiseen keinoel¨ am¨ a¨ an nyt ja hahmotelma • [A Review of 3D AL and Outline of its Future] [563] tulkinnassa Induktiivinen oppiminen metsänviljelyn tietokannan • [Inductive learning in interpretation of databases of forest cultivation] [93] Tutkimus A Study on the Use of GAs in Project Time Sheduling • geneettisten algoritmien kytst projektin aikataulutuksessa] [99] tutkittaessa Geneettisten algoritmien käyttö • sumean logiikan hy¨ oty¨ a PID-s¨ a¨ ad¨ oss¨ a - Esimerkkin¨ a taajuusmuuttajan sis¨ aiset s¨ a¨ at¨ aj¨ at [Evaluating the benefit of fuzzy logic for PIDcntr. by means of GAs - case: frequency cntr. ] [555] Two-dimensional and three-dimensional model-based matching using a minimum Rep. criterion and a hybrid GA [262] • time-domain inversion of perfect conductors using the GA [388] – Signal processing and image restoration techniques for • eddy current nondestructive evaluation [227] ultrafast Adaptive cntr. of the propagation of • light through random and nonlinear media [289] uncertainties Design for • of sheet metal forming process [50] Understanding Observing, • and cntr. the Gen. Method on a Neural Network Appl. [88] undirected Geneettisten algoritmien soveltaminen suuntaamattomien verkkojen piirtoon [Applying GAs to drawing • graphs] [414] unfolding GAs: a new technique for solving the neutron spectrum • problem [171] Uniform Modified • Crossover and Desegredation in GAs [282] Unitary Transformations for Quantum Computing [381] Universal Service: Issues on Modelling and Regulation [78] Unix Study of Covert Channels in a Trusted • Syst. [323] unrestricted The use of GAs to optimise chemical flowshops of • topology [304]

60

unterschaligen Simulation einer • Schwebewaage auf einem Analogrechner und Opt. ihres einsschwingverhaltens mit der ES [175] Untersuchung u ¨ ber die Anwendbarkeit der ES in der Nachrichtentechnik [196] • zur Anwendung eines Verfahrens der ES bei der Opt. von Leichtbaustrukturen [433] Untersuchungen Grundlegende empirische • der Parameter von ESn — Metastrategien [535] • u ¨ ber die m¨ oglichkeit der automatischen entwicklung von algebraischen Formeln aus Daten mit hilfe der ES [182] • zur Effizienz mehrgliedriger asynchroner ESn auf Transputersyst. en [226] Urinary Knowledge Discovery for Female • Incontinence Expert Syst. [96] – Parameter Evaluation and Gen. -Based Rule Learning for the Differential Diagnosis of Female • Incontinence [240] Usability Syst. • of Complex Tech. Syst. [400] usando Aprendizaje de reglas difusas • algoritmos gen´ eticos [Concept Learning trought GAs] [354] Utilizing Zeroth-Order Shape Opt. • a Learning Classifier Syst. [242] UV Studies in appl. computational chemistry: META model of photochemical reactions under • under nat. conditions and an MCASE appr. to the search of a cure for Parkinson’s disease [30] vaativien Taitoa • tehtävien oppiminen ja suoritus WorkPartner-robotilla [Learning and performing skill demanding tasks with WorkPartner robot] [484] validation Monte Carlo • of two gen. clustering alg. [22] VALMA VALMA-annoslaskentamallin rajoitettu optimointi geneettisell¨ a algoritmilla [Constrained Opt. of the • Dose Assessment Model by a GA] [22] VALMA-annoslaskentamallin rajoitettu optimointi geneettisell¨ a algoritmilla [Constrained Opt. of the VALMA Dose Assessment Model by a GA] [221] Variable Local Search and • Neighborhood Search Alg. for the Vehicle Routing Problem with Time Windows [250] variables Mixture-process experiments with cntr. and noise • [358] – Opt. of quantitative • in discrete event simulation models [248] – Response surface methods for experiments involving correlated noise • [561] variance GAs and fitness • with an appl. to the automated design of artificial neural networks [202] vector Design and opt. of optical diffractive elements using • space projections and pseudo random encoding [439] – Iterative and Hierarchical Methods for Codebook Generation in • Quantization [565] – Some experiments in machine learning using • evaluated GAs [15] Vehicle Alg. Library for Large Scale • Routing [575] vehicle routing Gideon: A GA syst. for • with time windows [106] vehicle routing problem A hybrid GA for the • with time windows [221] Vehicle Routing Problem Local Search and Variable Neighborhood Search Alg. for the • with Time Windows [154] Vektoroptimierung ESn f¨ ur die • [193] Verbesserung des Simulated Annealing unter Anwendung Genetischer Programmierung am Beispiel des Diskreten Quadratischen Layoutproblems [533] Verfahren Bionische • zur Entwicklung visueller Systeme [196] Verfahrens Untersuchung zur Anwendung eines • der ES bei der Opt. von Leichtbaustrukturen [506] Vergleich Ein • von Opt. sverfahren f¨ ur die zeitdiskrete Simulation [88] verkkojen Geneettisten algoritmien soveltaminen suuntaamattomien • piirtoon [Applying GAs to drawing undirected graphs] [165] verschiedener Einfluß • Wahrscheinlichkeitsverteilungen auf das Konvergenzverhalten von ESn [140]


[324]

version spaces

Opt. rate concept acquisition using •

and GAs

vertailu Hissien ohjausjärjestelmien tilastollinen • [A statistical comparison of two elevator call allocation method] [58] verteilt Ein • par. er genetischer Algorithmus [162] vertex Par. GA for the DAG • splitting problem [420] virology Computational biology: Methods in automated molecular docking with appl. in industrial • and antibody-antigen recognition [540] Virtual Evolving • Agents using Gen. Prog. [479] viscoelastically Gen. search methods for multicriterion opt. design of • damped structures [80] Vision-based Obstacle Avoidance: A Coevol. Appr. [533] visueller Bionische Verfahren zur Entwicklung • Systeme [429] VLSI-Based Evol. Strategies for the High-Level Synthesis of • DSP Syst. for Low Power [377] volatile Data analysis strategies for qualitative and quantitative determination of organic compounds by Fourier transform infrared spectroscopy (signal processing, pattern recognition, GAs, • organic compounds) [352] voltage Contingency ranking for • stability using a GA [37] – Multi-objective Reconfiguration of Medium • Distribution Networks [Keskij¨ anniteverkkojen kytkent¨ atilanteen monitavoitteinen jakorajaoptimointi] [311] VRPTC An empirical computational study of GAs to solve order based problems: An emphasis on TSP and • [109] wafer A finite capacity sch. syst. for a silicon • manufacturer [Hienokuormitusjrjestelm piikiekkovalmistajalle] [165] Wahrscheinlichkeitsverteilungen Einfluß verschiedener • auf das Konvergenzverhalten von ESn [168] Walsh function analysis of GAs of nonbinary strings [217] water Broadband nonlinear inversion for geoacoustic parameters in shallow • [283] Wavelet-Transformed Coding of • Images [299] weight GANNet: A GA for searching topology and • spaces in neural network design. The first step in finding neural network solution [486] Werkstoffverhalten Opt. balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und plastischem • [Opt. of beamlike cylindrical shells in reinforced concrete including elastic and plastic material behaviour] [575] windows Gideon: A GA syst. for vehicle routing with time • [508] wissensbasierter Ein • genetischer Algorithmus zur Rekonstruktion physicalischer Ereignisse [30] WorkPartner robot Taitoa vaativien tehtävien oppiminen ja suoritus WorkPartner-robotilla [Learning and performing skill demanding tasks with • [30] WorkPartner-robotilla Taitoa vaativien tehtävien oppiminen ja suoritus • [Learning and performing skill demanding tasks with WorkPartner robot] [112] Writing prog. using GAs [292] X-ray Novel Gen. Fitting Alg. and Statistical Error Analysis Method for • Reflectivity Analysis [296] X-ray Structure determination alg. in computational • crystallography [522] Xroute A knowledge-based routing syst. using neural networks and GAs [25] Zastosowanie operatorów ewolucyjnych do optymalizacji drzew binarnych [506] zeitdiskrete Ein Vergleich von Opt. sverfahren f¨ ur die • Simulation [354] Zeroth-Order Shape Opt. Utilizing a Learning Classifier Syst. [52] Zielfunktion Partielle Auswertung der • eines MPGA [468] Zuordnungsproblems Par. Ansatz zur Lösung des Quadratischen • [471] Zust¨ ande Ein Evolutionsverfahren zur mathematischen Modellierung station¨ arer • in dynamischen Systemen [486] Zylinderschalen Opt. balkenartiger • aus Stahlbeton mit elastischem und plastischem Werkstoffverhalten [Opt. of beamlike cylindrical shells in reinforced concrete including elastic and plastic material behaviour] [85]

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[579] Wen-Ruey Hwang. Intelligent control based on fuzzy algorithms and genetic algorithms. PhD thesis, New Mexico State University, 1993. * DAI 54/12 ga:WRHwangThesis. [580] R. Weinberg. Computer simulation of a living cell. PhD thesis, University of Michigan, Ann Arbor, 1970. †[638] ga:WeinbergThesis. [581] E. D. Weinberger. A stochastic generalization of Eigen’s model of natural selection. PhD thesis, New York University, 1987. (University Microfilms No. 87-22798) † ga:WeinbergerThesis. [582] Y. Xiong. Optimization of transportation network design problems using a cumulative genetic algorithm and neural networks. PhD thesis, University of Washington, WA, 1992. †ACM/93 ga:XiongThesis. [583] Yong Li. Heuristic and exact algorithms for the quadratic assignment problem. PhD thesis, The Pennsylvania State University, 1992. * DAI 53/12 ga:YLiThesis. [584] Yejin Zhou. Genetic algorithm with qualitative knowledge enchancement for layout design under continuous space formulation. PhD thesis, University of Illinois at Chicago, 1993. * DAI 54/12 ga:YZhouThesis. [585] James Milton Yunker. The optimization of simulation models by genetic algorithms: A comparative study. PhD thesis, Virginia Polytechnic Institute and State University, 1993. * DAI vol. 55 No. 3 ga:YunkerThesis. [586] Dirk Johannes Bank van der. The use of genetic algorithms for cryptanalysis. PhD thesis, University of Pretoria, South Africa, 1992. (in Afrikaans) * DAI 53/5 ga:vdBankThesis. [587] S. Pai, W. K. Jenkins, and D. J. Krusienski. Adaptive IIR phase equalizers based on stochastic search algorithms. In Proceedings of the 37th Asilomar Conference on Signals, Systems, and Computers, volume 1, pages 652–656, ?, 9.-12. November 2003. IEEE, Piscataway, NJ. ga03aSPai. [588] Egbert J. W. Boers, Marko V. Borst, and Ida G. Sprinkhuizen-Kuyper. Evolving neural networks using the “Baldwin effect”. In D. W. Pearson, N. C. Steele, and R. F. Albrecht, editors, Artificial Neural Nets and Genetic Algorithms, pages 333–336, Alès (France), 19.-21. April 1995. Springer-Verlag, Wien New York. ga95aBoers. [589] A. Chincarini, P. Fabbricatore, G. Gemme, R. Musenich, R. Parodi, and B. Zhang. Headway in cavity design through genetic algorithms. IEEE Transactions on Magnetics, 31(3):1566–1569, May 1995. (Proceedings og the Sixth Biennial IEEE Conference on Electromagnetics Field Computation (CEFC’94), Grenoble (France), 5.-7. July 1994) ga95aChincarini. [590] Tanja Dabs and Jochen Schoof. A graphical user interface for genetic algorithms. Report 98, Universit¨ at W¨ urzburg, Institut f¨ ur Informatik, 1995. ga95aDabs. [591] Mark´ us Gu∂mundsson, Essam A. El-Kwae, and Mansur R. Kabuka. Edge detection in medical images using a genetic algorithm. IEEE Transactions on Medical Imaging, 17(3):469–474, June 1998. ga98aGudmundsson. [592] Markus Schwehm. Optimierung der Partitionierung und Kanban-Zuordnung bei JIT-Fertigungsstraßen. In Jochen Kuhl and Volker Nissen, editors, Evolution¨ are Algorithmen in Management-Anwendungen, pages 11–20, G¨ ottingen (Germany), 23. February 1995. Georg-August-Universit¨ at G¨ ottingen. (in German) ga95aSchwehm. [593] Jaime J. Fernandez, Kristin A. Farry, and John B. Cheatham. Waveform recognition using genetic programming: The myoelectric signal recognition problem. In Koza et al. [644], pages 63–71. ga96aFernandez. [594] Ming-Suen Shyu and Jin-Jang Leou. A genetic algorithm approach to color image enchancement. Pattern Recognition, 31(7):871–880, July 1998. ga98aMing-SuenShyu. [595] Andrew Tuson and Peter Ross. Co-evolution of operator settings in genetic algorithms. In Terence C. Fogarty?, editor, Evolutionary Computing, Proceedings of the AISB96 Workshop, pages 291–300, Brighton, UK, 1.-2. April 1996. Springer-Verlag, Berlin (Germany). ga96aTuson. [596] Daniel S. Weile and Eric Michielssen. Genetic algorithm optimization applied to electromagnetics - a review. IEEE Transactions on Antennas and Propagation, 45(3):343–353, March 1997. (89 refs) ga97aWeile. [597] Weng-Tat Chan and David K. Chua. Civil engineering applications of genetic algorithms. In Jorge Vanegas and Paul Chinowsky, editors, Computing in Civil Engineering, pages 1072–1078, Anaheim, CA, 17.-19. June 1996. ga96bW-TChan. [598] Jih-Lian Ha, Rong-Wong Fung, and Chang-Fu Han. Optimization of an impact drive mechanism based on real-coded genetic algorithm. Sensors and Actuators A, 121(?):488–493, ? 2005. ga05aJih-LianHa. [599] Catherine Bounsaythip and Jarmo T. Alander. Genetic algorithms in image processing - a review. In Jarmo T. Alander, editor, Proceedings of the Third Nordic Workshop on Genetic Algorithms and their Applications (3NWGA), pages 173–192, Helsinki (Finland), 18.-22. August 1997. Finnish Artificial Intelligence Society (FAIS). (available via anonymous ftp site ftp.uwasa.fi directory cs/3NWGA file Bounsaythip.ps.Z) ga97aBounsaythip.

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[620] J. A. Vasconcelos, R. R. Saldanha, L. Krahenbuhl, and A. Nicolas. Genetic algorithm coupled with a deterministic method for optimization in electromagnetics. In Proceedings of the Seventh Biennial IEEE Conference on Electromagnetic Field Computation, page 289, Okayama (Japan), 18.-20. March 1996. IEEE, New York. †EEA 112153/96 ga96aVasconcelos. [621] R. Spallino, J. Cai, and G. Thierauf. Parallel evolution strategies in the optimal design of laminated beams. In B. H. V. Topping, editor, Advances in Computational Mechanics with Parallel and Distributed Processing (Proceedings of the First Euro-Conference on Parallel and Distributed Computing for Computational Mechanics), pages 203–208, Lochinver (Scotland), 26. April-1. May 1997. Civil-Comp Press, Edinburgh. ga97aSpallino. [622] Christian Jacob. Evolving evolution programs: Genetic programming and L-systems. In Koza et al. [644], page ? †conf.prog ga96aJacob. [623] Robert A. Richards and Sheri D. Sheppard. Three-dimensional shape optimization utilizing a learning classifier system. In Koza et al. [644], page ? †conf.prog ga96aRichards. [624] Dirk Thierens. Dimensional analysis of allele-wise mixing revisited. In Voigt et al. [648], pages 255–256. ga96aThierens. [625] E.-C. Yeh, S. S. Venkata, and Z. Sumić. Improved distribution system planning using computational evolution. In Proceedings of the 1995 IEEE Power Industry Computer Application Conference, pages 530– 536, Salt Lake City, UT, 7.-12. May 1995. IEEE, New York. ga95bYeh. [626] Marc Schoenauer. Shape representation for evolutionary optimization and identification in structural mechanics. In Winter et al. [647], pages 443–464. ga95aSchoenauer. [627] Carlos M. Fonseca and Peter J. Fleming. On the performance assessment and comparison of stochastic multiobjective optimizers. In Voigt et al. [648], pages 584–593. ga96aFonseca. [628] Peter F. Stadler and Robert Happel. Random field model for fitness landscape. Journal of Mathematical Biology, 38(?):435–467, ? 1999. (available via www URL: http://www.tbi.univie.ac.at/~ studla/publications.html) ga99aPeterFStadler. [629] Christian H¨ ohn and Colin R. Reeves. The crossover landscape for the onemax problem. In Jarmo T. Alander, editor, Proceedings of the Second Nordic Workshop on Genetic Algorithms and their Applications (2NWGA), Proceedings of the University of Vaasa, Nro. 11, pages 27–44, Vaasa (Finland), 19.-23. August 1996. University of Vaasa. (available via anonymous ftp site ftp.uwasa.fi directory cs/2NWGA file Reeves.ps.Z) ga96aHohn. [630] Stefan Voget. Theoretical analysis of genetic algorithms with infinite population size. Hildesheimer Informatikberichte 31/95, Universit¨ at Hildesheim, Institut f¨ ur Matematik, 1995. ga95bVoget. [631] George Duponcheele and D. G. Tilley. Topological optimization of a bumber beam via the messy genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Automobile Engineering, 212(D2):133– 143, 1998. ga98aDuponcheele. [632] John H. Holmes, Pier Luca Lanzi, Wolfgang Stolzmann, and Stewart W. Wilson. Learning classifier systems: New models, successful applications. Information Processing letters, 82(?):23–30, ? 2002. ga02aJHHolmes. [633] W. J. Pullan. Structure prediction of benzene clusters using a genetic algorithm. Journal of Chemical Information and Computer Sciences, 37(6):1189–1193, November/December 1997. ga97aWJPullan. [634] Jo˜ ao Pedro Pedroso. Niche search: An evolutionary algorithm for global optimisation. In Voigt et al. [648], pages 430–440. ga96aPedroso. [635] Richard R. Brooks, S. S. Iyengar, and Suresh Rai. Comparison of genetic algorithms and simulated annealing for cost minimization in a multisensor system. Optical Engineering, 37(2):505–516, February 1998. ga98aRRBrooks. [636] Daniel Erni, Dorothea Wiesmann, Michael M. Sp¨ uhler, Stephan Hunziker, Esteban Moreno, Benedikt Oswald, J¨ urg Fr¨ ohlich, and Christian Hafner. Application of evolutionary optimization algorithms in computational optics. ACES Journal, 15(2):43–60, ? 2000. ga00aDanielErni. [637] Mark Harman and Bryan F. Jones. Search-based software engineering. Information and Software Technology, 43(14):833–839, 15. December 2001. ga01aMHarman. [638] John H. Holland. ga:Holland92book.

Adaptation in Natural and Artificial Systems.

MIT Press, Cambridge, 1992.

[639] Hans-Georg Beyer. Simulation of steady states in dissipative systems by Darwin’s paradigm of evolution. Journal of Non-Equilibrium Thermodynamics, 15(1):45–58, 1990. ga:Beyer90.

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[640] J. Cai and G. Thierauf. Genetic algorithms and evolution strategies - comparison and combination. In B. H. V. Topping, editor, Advances in Computational Mechanics with Parallel and Distributed Processing (Proceedings of the First Euro-Conference on Parallel and Distributed Computing for Computational Mechanics), page ?, Lochinver (Scotland), 26. April-1. May 1997. Saxe-Coburg Publications, Edinburgh. ga97aJCai. [641] Jayshree Sarma and Kenneth A. De Jong. An analysis of the effects of neighborhood size and shape on local selection algorithms. In Voigt et al. [648], pages 236–244. ga96aSarma. [642] Patrick Monsieurs and Eddy Flerackers. Reducing population size while maintaining diversity. In Conor Ryan, Terence Soule, Maarten Keijzer, Edward Tsang, Riccardo Poli, and Ernesto Costa, editors, Genetic programming, 6th European Conference, EuroGP 2003 Proceedings, volume 2610 of Lecture Notes in Computer Science, pages 142–152, Essex (UK), 14.-16. April 2003. Springer-Verlag, Berlin. ga03aPMonsieurs. [643] Michael O. Odetayo. Replacing one or two individuals at a time during reproduction: An investigation. In Pavel Oˇsmera, editor, Proceedings of the MENDEL’95, pages 99–103, Brno (Czech Republic), 26.-28. September 1995. Technical University of Brno. ga95aOdetayo. [644] John R. Koza, David E. Goldberg, David B. Fogel, and Rick L. Riolo, editors. Proceedings of the GP-96 Conference, Stanford, CA, 28.-31. July 1996. MIT Press, Cambridge, MA. †prog ga96GP. [645] Ingo Rechenberg. Evolutionsstrategie: Optimierung technisher Systeme nach Prinzipien der biologischen Evolution. Frommann-Holzboog Verlag, Stuttgart, 1973. (reprint in [604]) † ga:Rechenberg73book. [646] Lance D. Chambers, editor. Practical Handbook of Genetic Algorithms, volume 1, Applications. CRC Press, Boca Raton, FL, 1995. ga95CRC1. [647] G. Winter, J. Périaux, M. Gal´ an, and P. Cuesta, editors. Genetic Algorithms in Engineering and Computer Science (EUROGEN95), Las Palmas (Spain), December 1995. John Wiley & Sons, New York. ga95LasPalmas. [648] Hans-Michael Voigt, Werner Ebeling, Ingo Rechenberg, and Hans-Paul Schwefel, editors. Parallel Problem Solving from Nature – PPSN IV, volume 1141 of Lecture Notes in Computer Science, Berlin (Germany), 22.-26. September 1996. Springer-Verlag, Berlin. ga96PPSN4.

Notations †(ref) = the bibliography item does not belong to my collection of genetic papers. (ref) = citation source code. ACM = ACM Guide to Computing Literature, EEA = Electrical & Electronics Abstracts, BA = Biological Abstracts, CCA = Computers & Control Abstracts, CTI = Current Technology Index, EI = The Engineering Index (A = Annual, M = Monthly), DAI = Dissertation Abstracts International, P = Index to Scientific & Technical Proceedings, PA = Physics Abstracts, PubMed = National Library of Medicine, BackBib = Thomas Bäck’s unpublished bibliography, Fogel/Bib = David Fogel’s EA bibliography, etc * = only abstract seen. ? = data of this field is missing (BiBTeX-format). The last field in each reference item in Teletype font is the BiBTEXkey of the corresponding reference.

Appendix A

Abbreviations The following other abbreviations were used to compress the titles of articles in the permutation title index: AI Alg. AL ANN(s) Appl. Appr. Cntr. Coll. Comb. Conf. CS(s) Distr. Eng. EP ES Evol. ExS(s) FF(s) GA(s) Gen. GP Ident. Impl.

= = = = = = = = = = = = = = = = = = = = = = = = =

Int. ImPr JSS ML Nat. NN(s) Opt.

Artificial Intelligence Algorithm(s) Artificial Life Artificial Neural Net(work)(s) Application(s), Applied Approach(es) Control, Controlled, Controlling, Controller(s) Colloquium Combinatorial Conference Classifier System(s) Distributed Engineering Evolutionary Programming Evolutionsstrategie(n), Evolution(ary) strategies Evolution, Evolutionary Expert System(s) Fitness Function(s) Genetic Algorithm(s) Genetic(s), Genetical(ly) Genetic Programming Identification Implementation(s)

OR Par. Perf. Pop. Proc. Prog. Prob. QAP Rep. SA Sch. Sel. Symp. Syst. Tech. TSP

91

= = = = = = = = = = = = = = = = = = = = = = = =

International Image Processing Job Shop Scheduling Machine Learning Natural Neural Net(work)(s) Optimization, Optimal, Optimizer(s), Optimierung Operation(s) Research Parallel, Parallelism Performance Population(s), Populational(ly) Proceedings Programming, Program(s), Programmed Problem(s) Quadratic Assignment Problem Representation(s), Representational(ly) Simulated Annealing Scheduling, Schedule(s) Selection, Selectionism Symposium System(s) Technical, Technology Travel(l)ing Salesman Problem

Appendix B

Bibliography entry formats This documentation was prepared with LATEX and reproduced from camera-ready copy supplied by the editor. The ones who are familiar with BibTeX may have noticed that the references are printed using abbrv bibliography style and have no difficulties in interpreting the entries. For those not so familiar with BibTeX are given the following formats of the most common entry types. The optional fields are enclosed by ”[ ]” in the format description. Unknown fields are shown by ”?”. † after the entry means that neither the article nor the abstract of the article was available for reviewing and so the reference entry and/or its indexing may be more or less incomplete. Book: Author(s), Title, Publisher, Publisher’s address, year. Example

John H. Holland. Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor, 1975. Journal article: Author(s), Title, Journal, volume(number): first page – last page, [month,] year. Example

David E. Goldberg. Computer-aided gas pipeline operation using genetic algorithms and rule learning. Part I: Genetic algorithms in pipeline optimization. Engineering with Computers, 3(?):35–45, 1987. †. Note: the number of the journal unknown, the article has not been seen. Proceedings article: Author(s), Title, editor(s) of the proceedings, Title of Proceedings, [volume,] pages, location of the conference, date of the conference, publisher of the proceedings, publisher’s address. Example

John R. Koza. Hierarchical genetic algorithms operating on populations of computer programs. In N. S. Sridharan, editor, Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89), pages 768–774, Detroit, MI, 20.-25. August 1989. Morgan Kaufmann, Palo Alto, CA. † . Technical report: Author(s), Title, type and number, institute, year. Example

Thomas B¨ ack, Frank Hoffmeister, and Hans-Paul Schwefel. Applications of evolutionary algorithms. Technical Report SYS-2/92, University of Dortmund, Department of Computer Science, 1992.

92

Vaasa GA Bibliography

93

Vaasa Genetic Algorithm Bibliography Search & Optimise Main features:

• Over 20,000 references to published papers • by over 20,000 researchers. • Available as over 70 special bibliographies online: ftp://ftp.uwasa.fi/cs/report94-1/ga*bib.pdf files. • Covers all sciences and engineering fields, from basic theory to applications. • Several indexes and statistical summaries. • See what problems evolution can solve for you! Global optimisation and search heuristics called genetic algorithm mimics evolution in nature using recombination and selection from a set of solution trials called population. One of the most prominent attractive features of genetic algorithms from the practical point of view of software techniques is their simplicity, which makes them easy to implement and tailor to solve practical search and optimisation problems. In spite of the seemingly simple processing, the genetic algorithms are good at solving some problems that are known to be hard. The simplicity, generality, flexibility, parallelism, and the good problem solving capability have made genetic algorithm very popular among various disciplines desperately searching methods to solve difficult optimisation problems.

————— Observe that our server has also a selection of our papers on genetic algorithms and other compuational topics. See our bibliographies or file ftp.uwasa.fi/cs/README for further details.

94

file ga90bib.ps.Z . . . ga02bib.ps.Z gaACOUSTICSbib.pdf gaAIbib.pdf gaAERObib.pdf gaAGRObib.pdf gaALIFEbib.pdf gaARTbib.pdf gaAUSbib.pdf gaBASICSbib.pdf gaBIObib.pdf gaCADbib.pdf gaCHEMbib.pdf gaCHEMPHYSbib.ps.Z gaCIVILbib.pdf gaCODEbib.pdf gaCOEVObib.ps.Z gaCONTROLbib.ps.Z gaCSbib.ps.Z gaEARLYbib.ps.Z gaEAST-EURObib.ps.Z gaECObib.pdf gaECOLbib.pdf gaELMAbib.pdf gaESbib.pdf gaFAR-EASTbib.ps.Z gaFEMbib.pdf gaFRAbib.ps.Z gaFTPbib.ps.Z gaFUZZYbib.ps.Z gaGEObib.ps.Z gaGERbib.ps.Z gaGPbib.ps.Z gaIMPLEbib.ps.Z gaINDIAbib.ps.Z gaINVERSEbib.ps.Z gaISbib.ps.Z gaJAPANbib.ps.Z gaLCSbib.ps.Z gaLASERbib.ps.Z gaLATINbib.ps.Z gaLOGISTICSbib.ps.Z gaMANUbib.ps.Z gaMATHbib.ps.Z gaMEDICINEbib.ps.Z gaMEDITERbib.ps.Z gaMICRObib.ps.Z gaMILbib.ps.Z gaMLbib.ps.Z gaMSEbib.ps.Z gaNANObib.ps.Z gaNIRbib.ps.Z gaNNbib.ps.Z gaNORDICbib.ps.Z gaOPTICSbib.ps.Z gaOPTIMIbib.ps.Z gaORbib.ps.Z


# refs . .. 557 181 2402 854 102 171 142 659 1040 1358 1314 886 2277 1068 377 232 1766 1453 723 679 1515 124 491 464 2066 73 462 1353 1453 312 1586 971 1291 276 244 81 2404 211 57 649 630 770 568 1810 83 111 897 490 109 163 1800 940 1643 923 1662

updated . .. 2008/03/19 2007/11/01 2009/01/07 2006/02/06 2003/07/09 2003/07/09 2008/05/22 2008/08/13 2008/08/11 2008/08/18 2004/09/20 2009/01/07 2008/03/20 2008/09/18 2008/03/12 2008/03/20 2008/03/12 2003/07/09 2009/01/07 2008/08/21 2009/01/07 2008/08/13 2003/07/09 2008/08/18 2003/07/09 2003/07/09 2008/03/11 2005/06/30 2004/09/22 2008/08/13 2003/07/09 2003/05/23 2008/08/11 2007/11/01 2008/05/22 2008/08/13 2008/09/09 2003/07/09 2003/07/09 2003/07/09 2009/01/07 2003/07/09 2008/03/31 2005/01/25 2007/11/02 2008/06/11 2008/04/07 2007/08/23 2008/03/12 2008/08/21 2008/07/28 2003/07/09 2008/08/14

...table continues on the next page...

contents GA in 1990 . .. GA in 2002 GA in acoustics (new: March 2008) GA in artificial intelligence GA in aerospace GA in agriculture (new) GA in artificial life GA in art and music GA in Australia and New Zealand Basics of GA GA in biosciences including medicine GA in Computer Aided Design GA in chemical sciences ; previously in gaCHEMPHYSbib.ps.Z GA in chemistry and physics; divided into gaCHEMbib.ps.Z and gaPHYSbib.ps.Z 2002 GA in civil, structural, and mechanical engineering GA coding co- and differential evolution GA(new) GA in control and process engineering GA in comp. sci. (incl. databases, /mining, software testing and GP) GA in yearly yeas (upto 1989) new GA in the Eastern Europe GA in economics and finance GA in ecology and biodiversity (new: 1.8.2008) GA in electromagnetics Evolution strategies GA in the Far East (excl. Japan) GA & FEM (new May 2008) GA in France GA papers available via web (ftp and www) GA and fuzzy logic GA in geosciences GA in Germany, Austria, and Switzerland genetic programming implementations of GA GA in India GA in inverse problems (new: Aug 2007) immune systems GA in Japan Learning Classifier Systems GA and lasers (new: April 2008) GA in Latin America, Portugal & Spain GA in logistics (incl. TSP) GA in manufacturing GA in mathematics GA in medicine (new: Nov 2007) GA in the Mediterranean GA in microscopy & microsystems (new: March 2008) GA in military applications GA in machine learning new GA in materials new GA in nanotechnology new GA in NIRS (spectroscopy) new GA in neural networks GA in Nordic countries GA in optics and image processing GA and optimization (only a few refs) GA in operations research


file gaPARAbib.ps.Z gaPARETObib.ps.Z gaPATENTbib.ps.Z gaPATTERNbib.ps.Z gaPHYSbib.ps.Z gaPIEZObib.ps.Z gaPOWERbib.ps.Z gaPROTEINbib.ps.Z gaQCbib.ps.Z gaREMOTEbib.pdf gaROBOTbib.pdf gaSAbib.pdf gaSCHEDULINGbib.pdf gaSELECTIONbib.ps.Z gaSIGNALbib.ps.Z gaSIMULAbib.ps.Z gaTELEbib.ps.Z gaTHEORYbib.ps.Z gaTHESESbib.ps.Z gaUKbib.ps.Z gaVLSIbib.ps.Z

# refs 766 406 458 1528 2313 51 940 491 539 275 745 307 785 273 2230 939 784 2483 578 1998 806

95

updated 2003/12/16 2003/07/09 2003/07/09 2007/11/06 2008/04/07 2008/03/26 2008/08/21 2008/03/12 2008/03/11 2008/08/11 2007/11/01 2003/07/09 2006/09/06 2007/09/20 2008/03/11 2003/07/09 2004/02/26 2008/08/13 2009/01/07 2008/05/22 2008/04/07

contents Parallel and distributed GA Pareto optimization GA patents GA in pattern recognition incl. LCS (new) GA in physical sciences ; previously in gaCHEMPHYSbib.ps.Z GA & piezo (new: March 2008) GA in power engineering GA in protein research quantum computing GA in remote sensing (new: 1.8.2008) GA in robotics GA and simulated annealing GA in scheduling Selection in GAs (new) GA in signal and image processing GA in simulation GA in telecom Theory and analysis of GA PhD etc theses GA in United Kingdom GA in electronics, VLSI design and testing

Table B.1: Indexed genetic algorithm special bibliographies available online in directory ftp://ftp.uwasa.fi/cs/report94-1. New updates also as .pdf files.

An Indexed Bibliography of Genetic Algorithm Theses

An Indexed Bibliography of Genetic Algorithm Theses

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