World Scientific Proceedings Series on
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Computer Engineering and Information Science 7
Uncertainty Modeling in Knowledge Engineering and Decision Making Proceedings of the 10th International FLINS Conference Istanbul, Turkey
26 – 29 August 2012
editors
Cengiz Kahraman Istanbul Technical University, Turkey
Etienne E. Kerre Ghent University, Belgium
Faik Tunc Bozbura Bahcesehir University, Turkey
World Scientific NEW JERSEY
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LONDON
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SINGAPORE
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BEIJING
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SHANGHAI
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HONG KONG
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TA I P E I
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CHENNAI
7/23/12 3:24 PM
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British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library.
World Scientific Proceedings Series on Computer Engineering and Information Science — Vol. 7 UNCERTAINTY MODELING IN KNOWLEDGE ENGINEERING AND DECISION MAKING Proceedings of the 10th International FLINS Conference Copyright © 2012 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system now known or to be invented, without written permission from the Publisher.
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ISBN 978-981-4417-73-0
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CONTENTS
Foreword
v
Invited Lectures
L-1
Fuzzy Relational Calculus and Its Wide Range of Applications Etienne E. Kerre
L-3
Decision Support and Warning Systems for Business Intelligence Jie Lu
L-5
A Review of Developments from Fuzzy Rule Bases to Fuzzy Functions I. Burhan Türkúen
L-8
Can Fuzzy Logic Formalism Bring Complex Environmental Issues into Focus? Ashok Deshpande
L-19
PART 1. DECISION MAKING AND DECISION SUPPORT SYSTEMS
1
Evaluation of Manufacturing Technology of Photovoltaic Cells E. Cables Pérez, M. T. Lamata Jiménez, J. L. Verdegay, M. S. Garcia-Cascales, J. M. Sánchez-Lozano
3
A Multicriteria Dynamic Flow Model for Relief Operations G. Tirado, B. Vitoriano, M. T. Ortuño
9
Future Oriented Positioning Analysis with Bayesian Networks Burak Dereli, Umut Asan, Çi÷dem Kadaifçi
15
Aggregation Procedure Based on Choquet Integral for Evaluating Company’s Environmental Practices R. De Andrés Calle, T. González-Arteaga
22
A Fuzzy Linguistic Evaluation Model of Digital Libraries Based on the LibQUAL+ Methodology F. J. Cabrerizo, M. A. Martínez, J. López-Gijón, E. Herrera-Viedma
28
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A Location-aware Tourism Recommender System Based on Mobile Devices José M. Noguera, Manuel J. Barranco, Rafael J. Segura, L. Martínez
34
Web Based Support System for Integral Performance Appraisal M. Espinilla, F. J. Martínez, L. Martínez, R. De Andrés Calle
40
Consensus in Preference-Approvals: A Weighted Distance Approach J. L. García-Lapresta, D. Pérez-Román, B. Erdamar, M. R. Sanver
46
A Fuzzy Envelope for Hesitant Fuzzy Linguistic Term Sets Based on Choquet Integral R. De Andrés Calle, T. González-Arteaga, R. M. Rodríguez, L. Martínez
52
Analysis of the Energy Service Market in Turkey Using the Fuzzy DEMATEL Method Ecem Basak, Umut Asan, Çi÷dem Kadaifçi
58
Replacement Decisions for Reliability Centered Maintenance D. Özgür-Ünlüakin, T. Bilgiç
64
A New Project Planning Model for Better Handling Vagueness and Uncertainty of Real World Tasks with AHP and Fuzzy Numbers Sibar Kaan Manga
70
Employing Cardinal Rank Ordering of Criteria in Multi-Criteria Decision Analysis Mona Riabacke, Mats Danielson, Aron Larsson, Love Ekenberg
76
Fuzzy Inference System for Net Present Value Analysis of Construction Projects Alp Ustundag, Emre Cevikcan
83
Combining Different Inference Methods for Medical Decision Support Systems Guven Kose, Hayri Sever, Mert Bal, Alp Ustundag
88
Decision Making for Concrete Evaluation Using Fusion of NDT Techniques Z. M Sbartaï, V. Garnier, M. A. Ploix
94
Multi-Period Decision Making with One-Shot Decision Theory Peijun Guo, Yonggang Li
100
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ix
Preference Intensity in MCDM When an Additive Utility Function Represents DM Preferences A. Mateos, A. Jimenez, E. A. Aguayo, P. Sabio
106
Fuzzy Topsis with Linguistic Evaluations Using Į–Cuts Seza Özge Gönen, Serdar Baysan
112
An Evolutionary Algorithm for Integer Multicriteria Optimization (EVALIMCO) Vassil Guliashki, Leoneed Kirilov, Krasimira Genova
118
The Applications of Energy Alternatives in Turkey Using Multicriteria Decision Making Processes Abit Balin, Pelin Alcan, Hüseyin Baúligil
124
A MCDM Model for Energy Policy Evaluation Mehmet Kabak, Metin Da÷deviren, Serhat Burmao÷lu
131
Project Selection by Using Fuzzy Topsis Method: A Real Application in Construction Sector Bersam Bolat, Gül Tekin Temur, Pinar Dursun, Burç Onursal
137
Location Selection of Emergency Logistics Centers Using an Integrated Dematel-Anp Approach Umut Rifat Tuzkaya, Kadriye Busra Yilmazer, Gulfem Tuzkaya
143
Garage Location Selection for Public Transportation System in Istanbul Using Fuzzy AHP and Fuzzy Axiomatic Design Techniques Özge Nalan Alp, Nurgül Demirtaú, Hayri Baraçli, Umut Rifat Tuzkaya
149
Evaluation of Criteria to Select Appropriate Candidates for Surgical Sciences Ipek Nur Aksu, F. Tunç Bozbura, Ahmet Beúkese
157
An Extended Method for Fuzzy Multiple Attribute Group DecisionMaking Based on Interval Type-2 Fuzzy Sets Zafer Eren, C. Erhan Bozdag
164
Group MCDM Method with Alternative Voting System Based on Multi-Information Environment Chen-Tung Chen, Chun-Che Huang, Ping-Feng Pai, Wei-Zhan Hung
171
A Ranking Methodology Using Hierarchical Grey Relational Analysis: The Case of Turkish Banking System Mehmet Emin Baysal, Büúra Aksu
177
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x
An Artificial Bee Colony Algorithm for Solving Nurse Scheduling Problems Ahmet Sarucan, Kadir Büyüközkan
183
A Greedy Algorithm for Multiobjective Fuzzy Flow-Shop Scheduling Problem Orhan Engin, M. Kerim Yilmaz, M. Cabir Akkoyunlu, M. Emin Baysal, Ahmet Sarucan
189
A Group Decision Making Model with Intuitionistic Fuzzy Preference Relations Hülya Behret
195
Fuzzy Analytic Hierarchy Process with Type-2 Fuzzy Sets Cengiz Kahraman, Irem Uçal Sari, Ebru Turanoglu
201
Fuzzy DEA Approach to Solve the Location Selection of Wind Energy Nihal Erginel, Merve Yalçinkaya, Sevil ùenturk
207
An Integrated Methodology Combining Fuzzy Goal Programming and Fuzzy AHP: Case of ELT in Turkey Yesim Kop, Mujde Erol Genevois, Hakki Ziya Ulukan
213
Prioritizing the Stakeholder Requirements in QFDE with FAHP Ilke Bereketli, Mujde Erol Genevois
219
Fuzzy Multi Attribute Valuation of Software Projects in Banking via Fuzzy Real Options Using Balanced Scorecard Ozlem Afacan, A. Cagri Tolga
225
A Cognitive Group Decision Support System for Projects Evaluation Fahimeh Ramezani, Jie Lu
231
Fuzzy Forecasting of Interest Rates in Investment Decisions Irem Uçal Sari, Cengiz Kahraman
237
Performance Evaluation of Turkish Retail Firms Using the Fuzzy AHP, Promethee, ELECTRE and VIKOR Methods Ufuk Bölükbaú, Erkan Çelik, Ali Fuat Güneri
243
Fuzzy Axiomatic Design Simulation for Evaluating the Conceptual Aircraft Designs Ahmet Kandakoglu, Cengiz Kahraman, Ilker Topcu
249
Criteria Weighing and 4P’s Planning in Marketing Using a Fuzzy Metric Distance and AHP Hybrid Method Tuncay Gürbüz, Y. Esra Albayrak, Elif Alaybeyo÷lu
255
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xi
Evaluation of Urban Regeneration Strategies Using VIKOR Method: The Case of Istanbul - Galata District Nihan C. Demirel, Ömer Onur Kaya, Tufan Demirel
261
Weighting the Criteria of Green Supply Chain Management for Supplier Selection in Automotive Industry Using Fuzzy ANP Serhat Tüzün, Tufan Demirel
267
Modelling a Pay Structure by Using Grey Relations Analysis Integrated with Fuzzy AHP Ahmet Can Kutlu
273
An Integrated Multi-Criteria Decision Making Methodology for Facility Location Selection Problem Under Fuzzy Environment: Application in Cement Sector Irem Otay, Ferhan Çebi
279
A Decision Support System for Two-Echelon Service Supply Chains Bariú Selçuk
285
A Fuzzy Analytic Hierarchy Process Methodology for the Supplier Selection Problem Pinar Mizrak Ozfirat, Gokcecicek Tuna, Gonca Tuncel
291
PART 2. UNCERTAINTY MODELING
301
Fuzzy Modeling and Optimization Angel Garrido, Piedad Yuste
303
Analyzing Maturity Levels of Turkish SMEs in Respect to ERP and Lean Manufacturing Applications: A Relational Model Ufuk Cebeci, Çagatay Iris
309
A Possibilistic Mathematical Programming Approach for Backbone Selection and Demand Allocation Problem in Telecom Networks H. H. Turan, N. Sener
315
A Modified QFD Technique for Product R&D Selcuk Cebi, Emrullah Demirci
321
An Incremental Collaborative Filtering Algorithm for Recommender Systems Maytiyanin Komkhao, Zhong Li, Wolfgang Halang, Jie Lu
327
A Judgement Method for Earthquake Early Warning Information Hongchang An, Jie Lu, Guangquan Zhang
333
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xii
Medical Skills Assessment in Training Based on Virtual Reality Using a Possibilistic Approach Liliane S. Machado, Ronei M. Moraes
339
A Novel Class-Attribute Interdependency Discretization Algorithm Hongliang Zheng, Li Zou, Deqin Yan
346
The Task of Minimum Cost Flow Finding in Transportation Networks in Fuzzy Conditions Alexandr Bozhenyuk, Evgeniya Gerasimenko, Igor Rozenberg
354
Path Identifying in Points-To Analysis for Java with Answer Set Programming Yang Bo, Zhang Ying, Zhang Ming-Yi
360
A Heuristic Based on Multi Objective Linear Programming Under Fuzziness for the Vehicle Routing Problem Gulcin Dinc Yalcin, Nihal Erginel
368
Rank Reversals and Testing of Pairwise Comparisons Based NonNumerical Rankings Ryszard Janicki, Yun Zhai
374
Modeling a Boiling Process By Means of a Takagi-Sugeno-FuzzyModel Daniel Fiss, Michael Wagenknecht, Rainer Hampel
382
A New Improved Bat Algorithm for Fuzzy Interactive Multi-Objective Economic/Emission Dispatch with Load and Wind Power Uncertainty Rasoul Azizipanah-Abarghooee, Taher Niknam
388
Handling Nonlinear Large-Scale Problems with Modified Firefly Algorithm Bahman Bahmanifirouzi, Abdollah Kavousi Fard, Taher Niknam
394
An Efficient Fuzzy Programming Approach to the Vehicle Routing Problem with Soft Time Windows Sezgin Kilic, Sezgin Kaplan
400
Enhance Green Supply Chain Management Capability to Develop an Eco-Friendly Enterprise: A Fuzzy QFD Approach Ching-Torng Lin
406
Agent-Based Modelling and Simulation Through Video Observation Analysis Shahrol Mohamaddan, Keith Case
412
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xiii
A Bayesian Framework for Uncertainty Formulation of Engineering Design Process M. Rajabalinejad, C. Spitas
418
Quantum Gates and Active Set Theory of Agents Germano Resconi, Chris Hinde
424
Mixture Augmented Lagrange Multiplier Method for Tensor Recovery Huachun Tan, Bin Cheng, Jianshuai Feng, Guangdong Feng, Wuhong Wang, Yu-Jin Zhang
430
Asymptotic Results for the Ergodic Distribution of an Inventory Model with Fuzzy Demands Tahir Khaniyev , Cihan Aksop, Baúak Gever
436
Process Chain Model for Corporate Social Responsibility Projects Funda Çinar, Esra Bas
442
Multi Mode Resource Constrained Project Scheduling Problems with Solving Taboo Search Omer Atli, Cengiz Kahraman
448
A Power Model of Enterprise Interests’ Allocation Xiaohong Liu
454
Evaluation of Airport Passenger Terminals Using Fuzzy Cognitive Mapping Çi÷dem Kadaifçi, Ilker Topcu
460
Implementation of Maximin and Maximal Solutions for Linear Programming Problems Under Uncertainty Nathan Huntley, Rolando Quiñones, Keivan Shariatmadar, Erik Quaeghebeur, Gert De Cooman, Etienne Kerre
465
A New C × K - Nearest Neighbor Linkage Approach to the Classification Problem Gözde Ulutagay, Efendi Nasibov
471
Analyzing Competitiveness of Automotive Industry Through Cumulative Belief Degrees Özgür Kabak, Füsun Ülengin, ùule Önsel, Özay Özaydin, Emel Aktaú
477
Using Surrogate Models for Process Design and Optimization A. Shokry, A. D. Bojarski, A. Espuña
483
A Chance Constrained Programming Model for Shortest Path Problem with Fuzzy Constraints Pinar Dursun, Erhan Bozdag
489
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xiv
Proactive and Reactive Scheduling with Fuzzy Activity Times Marek Janczura, Dorota Kuchta
495
Using Fuzzy Set Theory for Water Quality Evaluation of Wulihu Lake, China Yuankun Wang, Dong Sheng, Dong Wang, Jichun Wu
501
Newsvendor Problem with One-Shot Decision Theory Peijun Guo, Xiuyan Ma
507
A Two-Phased Additive Approach for Multiple Objective Supplier Selection with Fuzzy Demand Level Feyzan Arikan
513
Selection of Reverse Logistics Provider for a Paper Firm Jihene Jlassi, Abederrahman El Mhamedi, Habib Chabchoub
519
A Fuzzy Cognitive Map Application for Causes of Bullwhip Effect in Supply Chains Secil Ercan, Mine Isik, Seyda S. Asan, Gulgun Kayakutlu
525
Uncertainties and Handling Methods in Supply Chain: A Literature Review Erhan Yazici, Murat Baskak, Gülçin Büyüközkan
531
Uncertainty Modelling in Supply Chain Management: The Trend in the Use of Fuzzy Set Theory Özgür Kabak
541
Collaborative Partner Evaluation with Multi-Criteria Decision Making Techniques Jbid Arsenyan, Gülçin Büyüközkan
547
PART 3. FOUNDATIONS OF COMPUTATIONAL INTELLIGENCE
553
The Real Algebraic Normal Form: Fuzzy Boolean Logic Satisfying ǻf = 0 Michael Vielhaber
555
Multi-Expert Decision Making Using Logical Aggregation Ana Poledica, Aleksandar Rakicevic, Dragan Radojevic
561
On Evaluations of Propositional Formulas Whose Range is a Subset of Some Fixed Countable Ordered Field Dragan Doder, Zoran Ognjanoviü, Aleksandar Peroviü, Miodrag Raškoviü
567
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xv
Logical Aggregation for Modular Neural Networks in Currency Exchange Rate Forecasting Ivan Nesic, Aleksandar Rakicevic, Bratislav Petrovic, Dragan Radojevic
573
Extending AHP with Boolean Consistent Fuzzy Logic and Its Application in Web Service Selection Ivana Dragoviü, Nina Turajliü, Dragan Radojevic
579
Cut Systems in ȍ-Sets and Reflections JiĜí MoþkoĜ
586
Duality Principles in Residuated Lattices Irina Perfilieva
592
Interpolativity of "At Least–At Most" Models of Monotone Fuzzy Rule Bases: Multiple-Input Case Martin ŠtČpniþka, Balasubramaniam Jayaram
598
A Method for Solving Fuzzy Relation Equations in Complete Brouwerian Lattices Xiaobing Qu, Xue-Ping Wang, Feng Sun
608
Fuzzy Transform for Image Reconstruction Irina Perfilieva, Pavel Vlašánek, Michaela Wrublová
615
Remarks to Model Theory in Higher Order Fuzzy Logic Vilém Novák
621
Interval-Valued Fuzzy Relational Equations with Min-Implication Qing-Quan Xiong, Xue-Ping Wang
627
Fuzzy Lattice Reasoning (FLR) Classifier for Human Facial Expression Recognition S. E. Papadakis, V. G. Kaburlasos, G. A. Papakostas
633
Fuzzy Cosets of Fuzzy Subgroups Relative to Fuzzy Subgroups Lan Shu, Zhaohao Wang
639
Two Topological Operators of Fuzzy Finite Automata Zhiwen Mo, Na Feng
645
On Fuzzy Rough Concept Lattices Chang Shu, Zhi Wen Mo
652
Study on the N-Inequality in the Lattice Implication Algebra*II Long Xiqing, Xu Yang, He Xingxing
658
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xvi
The Product of Quantum Automata Mo Zhi-Wen, Chen Qing-Lei, Liu Jun
664
Image Matching Based on Medium Similarity Measure Ningning Zhou, Long Hong
670
Feature-Based Off-Line Recognition of Degraded Numeral Characters Weiqing Cheng, Long Hong, Feier Zhu, Xiang Li, Jian Li
676
On Measure Method to the Two-Phase Uncertainty and Its Application Yulong Deng, Long Hong
684
Filters and deductive systems on residuated multilattices I. P. Cabrera, P. Cordero, G. Gutiérrez, J. Martínez, M. Ojeda-Aciego
690
ǹ-Multi Ary Semantic Resolution Methods Based on Lattice-Valued Propositional Logic LP(X) Yi Liu, Xiaoyan Qin, Yang Xu
696
An Optimal Spectrum Allocation Scheme Based on Stackelberg Game in Macro/Femtocell Hierarchical Networks Peng Xu, Yang Xu
702
A Study on Fuzzy D-Implications A. G. Hatzimichailidis, G. A. Papakostas, V. G. Kaburlasos
708
Research Advances on Resolution Automated Reasoning in LatticeValued Logic Based on Lattice Implication Algebra Yang Xu, Xiaomei Zhong, Xingxing He, Jun Liu
714
General Form of ǹ-Linear Resolution Method Based on Lattice-Valued Propositional Logic System LP(X) Weitao Xu, Dexian Zhang, Hua Zhu, Yang Xu
720
N-Truth Degrees of Formulae in Two-Valued Predicate Logic Qin Xiaoyan, Liu Yi, Xu Yang
726
Auto-Associative Memories Based on Complete Inf-Semilattices Peter Sussner, Carlos Renato Medeiros
732
An Extended Variable Consistency Model Under Dominance-Based Rough Sets Dun Liu, Tianrui Li
738
Lifting Quasi-Filters of Lattice Implication Algebras Xiaodong Pan, Xiaohong Liu
744
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xvii
Intuitionistic Fuzzy Propositional System Based on Linguistic TruthValued Intuitionistic Fuzzy Lattice Li Zou, Xin Liu, Dengen Huang
750
Fuzzy Membership Function Construction Based on Multi-Valued Evaluation Vasile Patrascu
756
Interval Identification of Uncertain Nonlinear Systems Using Belief Rule-Based Systems Yu-Wang Chen, Dong-Ling Xu, Jian-Bo Yang
762
Construction of Strong Equality Index From Implication Operators H. Bustince, J. Fernandez, J. A. Sanz, D. Paternain, M. Baczyski, G. Beliakov, R. Mesiar
769
On Derivations of Lattice Implication Algebras Hua Zhu, Jianbin Zhao, Weitao Xu, Yang Xu
775
Some Remarks on a Numerical Representation Theorem By Newman and Read J. C. Candeal, E. Induráin, G. B. Mehta
781
Conditional Choquet Expectation Hongxia Wang, Shoumei Li, Juan Gao
787
Ascribing Strong Causes From Observational and Interventional Data Under the Belief Function Framework Imen Boukhris, Salem Benferhat, Zied Elouedi
794
SMOTE-FRST: A New Resampling Method Using Fuzzy Rough Set Theory E. Ramentol, N. Verbiest, R. Bello, Y. Caballero, C. Cornelis, F. Herrera
800
Dealing with Natural Language Interfaces in a Geolocation Context Mohammed-Amine Abchir, Isis Truck, Anna Pappa
806
Induced and Heavy Aggregation Operators José M. Merigó, Yejun Xu
812
PART 4. STATISTICS, DATA ANALYSIS AND DATA MINING
819
Forecasting High Frequency Financial Data: Statistical and Fuzzy Logic RBF ANN Approach Dusan Marcek
821
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xviii
Statistical Models, SV Regression Models and Soft Neural Networks: An Application to the Input-Output Function Estimation of Sales Processes Dusan Marcek
827
A Hybrid Approach to Selecting Informative Constraints for SemiSupervised Clustering Xianhua Ni, Yan Yang
833
Analysis of the Impacts of the Data Length on the Uncertainty of the Archimedean Copula Modeling Tong Xin, Wang Dong, Chen Yuanfang
839
An Initial Research to Segment a Crowdsourcing Project Participants Using Text Mining Baúar Öztayúi, Lara Cemcem
845
Spare Part Demand Forecasting with Bayesian Model Sinan Apak
851
Decision Making in Complex Environments with Uncertain Generalized Unified Aggregation Operators José M. Merigó
857
Software Cost Estimation By Fuzzy Analogy for ISBSG Repository Ali Idri, Fatima Azzahra Amazal
863
Probabilistic Kernel Ranking Bernd-Jürgen Falkowski
869
Probabilistic Operation Management for a Microgrid Based on Point Estimate Method and Modified Gravitational Search Algorithm Masoud Jabbari, Faranak Golestaneh, Taher Niknam
875
Effectiveness Evaluation of Complex Networks: A Simulation-Based Algorithm Wuhong Wang, Fuguo Hou, Rongjie Lin, Fang Li
881
A New “Implicit” Parameter Estimation for Conditional Gaussian Bayesian Networks Aida Jarraya, Afif Masmoudi, Philippe Leray
887
Dissimilarity-Based Bipolar Supervised Classification J. Tinguaro Rodríguez, Javier Montero, Begoña Vitoriano
894
Using Group Method of Data Handling for Brain Computer Interface Ravikanth Varaganti, Vitaly Schetinin
900
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xix
UApriori: An Algorithm for Finding Sequential Patterns in Probabilistic Data Metanat Hooshsadat, Samaneh Bayat, Parisa Naeimi, Mahdieh S. Mirian, Osmar R. Zaïane
907
Seasonal Variation of Turkey: A Consensus Clustering Approach Ayca Yetere Kursun, Cem Iyigun, Ceylan Yozgatligil, Inci Batmaz
913
Spatial Analysis Based Method for Detection of Data Traffic Problems in Computer Networks Grzegorz Kolaczek
919
Uncertainty and a New Measure for Classification Uncertainty Haluk Damgacio÷lu, Cem Iyigün
925
A New Process Monitoring Control Chart Su-Fen Yang, Chung-Ming Yang
931
Forecasting Future Enrollments to Universities of North Cyprus Through Trend Centrality Based on Fuzzy Time Series Ebru Turanoglu, Ozlem Senvar
937
Fuzzy Expert System for Forecasting Return Amount in Reverse Logistics Gül Tekin Temur, Muhammet Balcilar, Bersam Bolat
942
PART 5. INTELLIGENT INFORMATION PROCESSING
949
Rainfall-Runoff Modeling Using Artificial Neural Networks and Adaptive Neuro-Fuzzy Inference System Models Gholamali Ghafari, Mehdi Vafakhah
951
Fuzzy Rule-Based Demand Forecasting for Dynamic Pricing Özlem Coúgun, Yeliz Ekinci, Seda U÷urlu
957
Neural Network and Parameter Production Modeling: Metaheuristics Clustering Methods A. F. Bernate Lara, F. Dugardin, F. Yalaoui, F. Entzmann
963
In-Core Sensors Readings Diagnostics Based on Neuro-Fuzzy Techniques Stefan Figedy
969
An Approach for Attribute Reduction in Set-Valued Ordered Information Systems Based on Information Entropy Chuan Luo, Tianrui Li, Hongmei Chen, Junbo Zhang
975
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Hybrid Simulated Annealing/Genetic Algorithm Approach to Buffer Allocation Problem in Unreliable Production Lines Simge Yelkenci Kose, Ozcan Kilincci
981
A Substitute Keyword Suggestion Method for Search Engine Advertising Qiang Wei, Jin Zhang, Guoqing Chen, Xunhua Guo
987
Supporting Situation Awareness Using Neural Network and Expert System Mohsen Naderpour, Jie Lu
993
Making Intelligent Decisions on Noisy Images Gonzalo Farias, Sebastián Dormido-Canto, Matilde Santos, Jesús Vega
999
SME Clustering Based on Innovation Needs Ayca Altay, Didem Cinar, Gulgun Kayakutlu, Irem Duzdar
1005
Artificial Neural Network for Discrete Model Order Reduction with Frequency Selectivity Othman M. K. Alsmadi, Zaer. S. Abo-Hammour, Adnan M. Al-Smadi
1011
Response of Soil-Structure Interaction System Using Artificial Neural Network (ANN) Badreddine Sbartai, Kamel Goudjil
1017
Recognition of Individuals Based on Hand Geometry Silarbi Samiya, Bendahmane Abderrahmane, Benyettou Abdelkader
1023
An New Belief Rule Base Representation Scheme and Its Generation By Learning From Examples J. Liu, L. Martínez, H. Wang, A. Calzada, S. W. Chen
1030
Estimation of Prediction Intervals of Neural Network Models By a Multi-Objective Genetic Algorithm Ronay Ak, Yanfu Li, Enrico Zio
1036
PART 6. PRODUCTIVITY AND RELIABILITY
1043
Load Average Forecast: A New Monitor to Analyse Instability in Computer Systems Victoria Lopez, Guadalupe Miñana
1045
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xxi
Computation of Component Importance Measures for Reliability of Complex Systems Qamar Mahboob, Faisal Maqbool Zahid, Eric Schöne, Michael Kunze, Jochen Trinckauf
1051
On the Revision to the Result of Finance Early-Warning Logit Model From the Perspective of Efficiency Shuangjie Li, Shao Wang
1058
Fuzzy AHP/DEA Approach for Relative Efficiency of State University in Turkey Ahmet Çalik, Nimet Yapici Pehlivan, Ahmet Pekgör
1064
Improving the Computational Complexity and Weights Dispersion in Fuzzy DEA Saber Saati, Adel Hatami-Marbini
1070
General DEA with Fuzzy Data Hilda Saleh, Mohsen Rostamy-Malkhalifeh, Zohreh Moghaddas
1076
Efficiency Analysis Under Imprecise Inputs and Outputs Reduction Kobra Gholami, Farhad Hosseinzadeh Lotfi, Adel Hatami-Marbini, Per J Agrell, Zahra Ghelej Beigi
1082
Resource Allocation and Target Setting in Interval Data Envelopment Analysis Zahra Ghelej Beigi, Farhad Hosseinzadeh Lotfi, Adel Hatami-Marbini, Per J Agrell, Kobra Gholami
1087
Project Risk Management Taking Into Consideration the Influence of Various Risk Levels Based on Linguistic Approach Dorota Kuchta, Dariusz Skorupka
1093
Risk Assessment of the Spanish National Railway System A. Mateos, A. Jimenez, H. J. Pichardo
1099
Performance Evaluation of Lot Sizing Strategy via Discrete Event Simulation Serdar Baysan, Cagatay Iris, Mehmet Mutlu Yenisey
1105
PART 7. APPLIED RESEARCH
1111
A Heuristic Approach for Provider Selection and Task Allocation Model in Telecommunication Networks Under Stochastic QOS Guaranties Hasan Huseyin Turan, Nihat Kasap
1113
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xxii
A New Architecture for Assessment of Multiple Users in Collaborative Medical Training Environments Based on Virtual Reality Ronei M. Moraes, Liliane S. Machado
1119
Large-Scale Spatial Grassland Fire Spread Simulation Based on GIS Xingpeng Liu, Jiquan Zhang, Zhijun Tong
1125
Decomposing Relation Schemes of Group-Buying Aggregators in ECommerce: A Reverse Engineering Approach Ming Ren, Qiang Wei
1131
A Bibliometric Exploration of the Evolution of 3D Technology Gizem øntepe, Tufan Koç
1137
ANFIS Model for Vibration Signals of an Induction Motor Based on Aging Process Decreasing the Nonlinearity D. Bayram, S. ùeker
1143
Modelling the Solid Fraction Transport of a Fiber Suspension with Cellular Automata Stefan Kittan, Wolfgang Kaestner
1149
Reducing EMI in Multiple-Output DC Converters with Chaos Control Yuhong Song, Zhong Li, Junying Niu, Guidong Zhang, Wolfgang Halang, Holger Hirsch
1155
An Application of Filled Function Method to the Hardness Property of Fe-Mn Binary Alloys Ahmet Sahiner, Havva Gokkaya
1161
Shedding Light on the Underlying Long-Run Price Leadership: A Study of US Gasoline Price Data Takamitsu Kurita
1167
Individual Assessment Model of the Public Spreading in the Environmental Pollution Accident Bin Luo, Xiaohong Liu, Xiaodong Pan
1173
Neutron Power Control of a Triga Mark III Reactor Using Stable Adaptive Fuzzy Control Benítez-Read, Jorge S., Rojas-Ramírez, Erick, Quintana-Carapia, Gustavo
1179
A Framework Proposal Upon the Estimation of Electronic-Waste Products in Istanbul Tugba Efendigil, Vildan Ozkir, Nihan C. Demirel, Tufan Demirel, Onder Ondemir
1184
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xxiii
Variance Reduction for Financial Options Pricing Semih Yön, Cafer Erhan BozdaЂ
1190
Learning Capabilities and their Effect on Organizational Capabilities: An Empirical Approach Sezi Çevik Onar
1196
Ensemble of Neural Networks for Detection and Classification of Faults in Nuclear Power Systems Roozbeh Razavi-Far, Piero Baraldi, Enrico Zio
1202
An Area Defuzzification Technique and Essential Fuzzy Rules for Defuzzifying Nuclear Event Failure Possibilities Into Reliability Data Julwan Hendry Purba, Jie Lu, Guangquan Zhang
1208
Multivariable Robust Control System: Application to a Plasma Reactor Karima Chaker, Abdelkrim Moussaoui
1214
Application of Genetic Algorithms to the Optimization of the Robustness of Controllers Matilde Santos, Nicolás Antequera
1221
A Hybrid Ensemble Approach for Process Parameter Estimation in Offshore Oil Platforms Piero Baraldi, Francesca Mangili, Enrico Zio, Giulio Gola, Bent H. Nystad
1227
Heuristic GP Optimization Technique for Design Synthesis of Monotonic Objectives Sayed M. Metwalli
1233
Quadcopter See and Avoid Using a Fuzzy Controller M. A. Olivares-Mendez, Luis Mejias, Pascual Campoy, Ignacio Mellado-Bataller
1239
Decision Fuzzy System on the State of Delayed Vehicles Matilde Santos, Manuel G. Romana
1245
Visual Interpretation of Fabric Tactile Properties Using Fuzzy Inclusion Degree and ANFIS Zhebin Xue, Xianyi Zeng, Ludovic Koehl, Yan Chen
1251
Fuzzy Logic Assisted Helicopter UAV Flight Control A. J. Van Der Wal
1257
Making Presentations Using Fuzzy Logic in a Tour-Guide Robot J. Javier Rainer, Ramón Galán, Agustín Jiménez
1263
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A Small World Optimization for Multiple Objects Optimization of Mixed-Model Assembly Line Problem with Parallel Machine ùükran ùeker, Mesut Özgürler
1269
A Hybrid Bees Algorithm for Solving a Robotic Assembly Line Balancing Problem Slim Daoud, Farouk Yalaoui, Lionel Amodeo, Hicham Chehade, Philippe Duperray
1275
Throughput Analysis of Two-Machine-One-Buffer Line Model: A Comparative Study Yassine Ouazene, Alice Yalaoui, Hicham Chehade
1281
Mixed Model Assembly Line Balancing with Subassembly Selection in Automotive Industry Rifat Gurcan Ozdemir, Ufuk Kula
1287
Matheuristics for the Multi-Item Lot-Sizing with Vehicle Routing Problem Heitor Liberalino, Christophe Duhamel, Alain Quilliot
1293
Scheduling Job and Preventive Maintenance to Obtain Trade-Off Between Cmax and Availability of 2-Level Flow-Shop F. Hnaien, F. Yalaoui
1299
A Multi-Objective Method to Solve a Container Terminal Problem Farah Belmecheri-Yalaoui, Farouk Yalaoui, Lionel Amodeo
1305
Fuzzy Chance Constrained Programming for Warehouse Location Problem with Imprecise Customer Demand Ceren Buket Kayi, Erhan Bozdag
1311
AUTHOR INDEX
1317
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IMPROVING THE COMPUTATIONAL COMPLEXITY AND WEIGHTS DISPERSION IN FUZZY DEA SABER SAATI* Department of Mathematics, Tehran-North Branch, Islamic Azad University, P.O. Box 19585-936, Tehran, Iran ADEL HATAMI-MARBINI LSM, Center of Operations Research and Econometrics (CORE), Universite catholique de Louvain, 34 Voie du Roman Pays, L1.03.01, B-1348 Louvain-la-Neuve, Belgium One of the prominent features of standard and fuzzy data envelopment analysis (DEA) is the representation of each of the participating decision making units (DMUs) in the best possible light. This causes two problems; first, the different set of factor weights with large number of zeros and second a large number of linear programming models to solve. In this paper, we propose an efficient method to address these two problems. In proposed method by solving just one linear programming a Common Set of Weights (CSW) is achieved in fuzzy DEA. Since resulted efficiencies by the proposed CSW are interval numbers rather than crisp values, it is more informative for decision maker. The proposed model is applied to a numerical example to demonstrate the concept.
1. Introduction Data envelopment analysis (DEA) [1] is a widely used non-parametric frontier analysis method, implemented in linear programming, for comparing the inputs and outputs of a set of comparable decision making units (DMUs). The flexibility of the DEA models, i.e. the absence of a priori assumptions on the production technology, is implemented through a minimal spanning hull. This flexibility in combination with the number of input and output dimensions normally render a relatively high proportion of the DMUs fully technically efficient, in particular for limited datasets. Between these value-free and value-exact approaches, Thompson et al. [2] used boundary conditions (bounds) for the virtual multipliers in DEA standard models. Solutions to these models identified only one efficient DMU for location of the lab in Texas. A series of possible approaches for setting bounds on factor weights in DEA have been put forward [2-3]. *
Email:
[email protected]
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Imposing bounds on factor weights, limits the flexibility of DEA in assigning individual sets of weights to each of the participating DMUs. In the extreme case, when no flexibility is allowed, a common set of weights (CSW) is applied for the assessment of all DMUs [4-7]. In this paper, we propose an algorithm to reduce the computational complexities and costs as well as overcoming pitfalls in the fuzzy DEA including the zero-value and differing weights and multiple solutions. Initially, we determine the lower and upper bounds of factor weights by comparing the data. We then use a linear programming problem to determine a CSW. Finally, we calculate the efficiency of the DMUs with the obtained CSW as intervals. The proposed models are applied to a numerical example. The remainder of this paper is organized as follows. In Section 2 we present the basic DEA models. In Section 3 we present the details of our proposed method and Section 4 contains a numerical example. The paper is closed in Section 5 with conclusions and some suggested future research directions. 2. Basic DEA Models Let us assume that there are n DMUs to be evaluated where each DMUj, j = 1,2,..., n convert m inputs into s outputs. Suppose xij (i = 1,!, m , j = 1,! , n) and yrj (r = 1,! , s , j = 1,! , n) are the ith input and the rth output of DMUj, respectively. The relative efficiency of DMUP, p ∈ {1,2,..., n} , is defined as the maximum value of θ p and can be obtained by using the following programming model (for constant returns to scale, CRS) [1]: s
max θ p = m
s.t.
¦u y
r rp
r =1
¦v x
i ip
i =1 s
=1 m
¦u y − ¦ v x r rj
r =1
i ij
i =1
ur , vi ≥ 0,
≤ 0,
∀j , ∀r , i.
(1) The relative efficiency of DMUP is determined by assigning weights to the inputs and outputs of the DMU and maximizing the ratio of the weighted sum of outputs to the weighted sum of inputs. The only underlying assumption for the weights of the inputs and outputs is non-negativity which is recognized as either a weakness or strength of the traditional DEA models. In addition, with respect to weights flexibility, some of input and output weights take the zero values. In the original DEA and its extensions, all the inputs and outputs assume the form
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of specific numerical values. In many real-world problems, however, the data can be imprecise or vague or described by qualitative terms. Fuzzy logic and fuzzy sets can represent imprecise or ambiguous data in DEA by formalizing inaccuracy in decision making [8]. The fuzzy CCR model with bounded factor weights is as follows:
max θ p =
s
¦ u y
r rp
r =1
m
¦ v x
s.t.
i ip
= 1,
i =1 s
¦
m
ur yrj −
r =1
¦ v x
i ij
≤ 0,
∀j,
i =1
U rl ≤ ur ≤ U ru ,
∀r , Vi l ≤ vi ≤ Viu , ∀i.
(2) where, U rl , U rl , U rl and U rl are lower and upper bounds on output and input weights, respectively. Note that in the fuzzy CCR model (2) the right hand sides of the constraints are assumed to be crisp values because they are similar to the original CCR model used for normalization of the value of the efficiency in the objective function. 3. Proposed Model In this study we use triangular fuzzy numbers to develop our model. However, our model is adaptable to other types of fuzzy numbers. To assess a CSW, an upper bound is determined for each factor. This is done by considering the following problems: max u p (or vt ) m
s.t.
¦ v ~x
i ij
i =1 s
¦ r =1
≤1
ur ~ yrj −
m
¦ v ~x
i ij
i =1
ur , vi ≥ 0,
≤ 0,
∀j , ∀r , i.
(3) The following model, therefore, can be obtained when fuzzy coefficients in model (3) are assumed to be triangular fuzzy numbers denoted as ~ xij = ( xijl , xijm , xiju ) and ~ yrj = ( yrjl , yrjm , yrju ) :
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max u p
(or vt )
m
¦v (x , x
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s.t.
l ij
i
m u ij , xij )
≤ 1,
i =1 s
¦
∀j , m
ur ( yrjl ,
r =1
yrjm ,
ur , vi ≥ 0,
yrju )
−
¦v (x , x i
i =1
l ij
m u ij , xij )
≤ 0,
∀j ,
∀r , i.
(4)
By introducing Į-cuts of constraints, the following model is obtained:
max u p
(or vt )
m
s.t.
¦[αx
+ (1 − α ) xijl , αxijm + (1 − α ) xiju ]vi ≤ 1
m ij
∀j ,
i =1 s
¦[αy
m rj
+ (1 − α ) yrjl , αyrjm + (1 − α ) yrju ]ur
r =1 m
−
¦ [αx
m ij
i =1
+ (1 − α ) xijl , αxijm + (1 − α ) xiju ]vi ≤ 0,
u r , vi ≥ 0,
∀j ,
(5)
∀r , i.
Since (5) has a special structure, so the upper and lower bounds of weights may achieved by comparing their constraints [9]. Since the weights are restricted to non-negativity, hence the lower bound of weights is zero, that is Vil = 0 and U rl = 0 (∀i, r ) . Considering the first constraints of (6), the upper bounds of input weights are calculated as follows:
° ½° 1 Vt u = min ® m ¾ l 1≤ j ≤ n α x + (1 − α ) x ° tj ¿ ¯° tj
(6)
And using the second constraints of (6), the upper bounds of output weights are determined as follows:
m m u u ½ °° ¦ [α xij + (1 − α ) xij ]Vi °° U up = min ® i =1 ¾ m l 1≤ j ≤ n ° α y pj + (1 − α ) y pj ° °¯ °¿
(7)
Starting from bounded model (2), a CSW can be achieved by expressing the deviation from either bound as a fraction of the range between the upper and lower bounds. Assuming the same deviation from bounds across all DMUs and applying Saati et al. [6] method, we get:
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max φ m
s.t.
¦ xˆ
ij
≤1
∀j ,
i =1
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s
m
¦ yˆ − ¦ xˆ rj
ij
r =1
≤ 0,
∀j ,
(8)
i =1
[α xijm + (1 − α ) xijl ]vi ≤ xˆij ≤ [α xijm + (1 − α ) xiju ]vi
∀i, j ,
[α y + (1 − α ) y ]ur ≤ yˆ rj ≤ [α y + (1 − α ) y ]ur
∀r , j ,
m rj
l rj
m rj
ur , vi ≥ 0,
u rj
∀r , i.
A CSW is obtained by solving (8), and the interval efficiency of each DMU can be evaluated as follows: s ª s * * m l m u º « ¦ ur ª¬α yrj + (1 − α ) yrj º¼ ¦ ur ª¬α yrj + (1 − α ) yrj º¼ » l u » ∀j e j = [e j , e j ] = « r =m1 , r =m1 * m l « v* ªα x m + (1 − α ) xu º vi ¬ªα xij + (1 − α ) xij ¼º » ¦ i ¬ ij ij ¼ «¬ ¦ »¼ i =1 i =1
where,
(9)
ur* (r = 1,..., s) and vi* (i = 1,..., m) are optimal values of (8).
4. Numerical Example In this section, we use the proposed method and demonstrate the applicability of our framework and exhibit the simplicity and efficacy of the procedures with an example. In this illustration, we address a problem with 10 hypothetical DMUs introduced in [7]. The resulted upper bounds of output and input weights are presented in Table 1. Table 1. The CSW by proposed model. Į 0.1 0.3 0.5 0.7 0.9 1
Iu1 0.0581 0.0568 0.0556 0.0543 0.0532 0.0526
Upper bounds Iu2 Ou1 0.0055 0.0172 0.0055 0.0164 0.0054 0.0155 0.0054 0.0147 0.0054 0.0140 0.0054 0.0136
Ou2 0.0016 0.0016 0.0015 0.0014 0.0014 0.0014
v1 0.0388 0.0379 0.0370 0.0362 0.0355 0.0351
Factor weights v2 u1 0.0037 0.0044 0.0036 0.0042 0.0036 0.0040 0.0036 0.0037 0.0036 0.0036 0.0036 0.0035
u2 0.0004 0.0004 0.0004 0.0004 0.0004 0.0003
Table 2. The corresponding efficiencies by CSW. DMU A B C D E E G H I J
Į 0.1 [0.2467,0.3093] [0.4107,0.5099] [0.3843,0.5421] [0.3037,0.4259] [0.7641,0.9735] [0.5414,0.6978] [0.3343,0.4237] [0.5587,0.7863] [0.2207,0.2589] [0.3045,0.3795]
0.3 [0.2479,0.2956] [0.4045,0.4778] [0.3872,0.5054] [0.3053,0.3968] [0.7641,0.9226] [0.5407,0.6585] [0.3315,0.3982] [0.5520,0.7178] [0.2175,0.2460] [0.2987,0.3537]
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0.5 [0.2491,0.2825] [0.3982,0.4480] [0.3902,0.4715] [0.3069,0.3698] [0.7641,0.8743] [0.5400,0.6216] [0.3288,0.3744] [0.5452,0.6564] [0.2142,0.2338] [0.2930,0.3300]
0.7 [0.2503,0.2699] [0.3920,0.4204] [0.3931,0.4401] [0.3085,0.3448] [0.7641,0.8285] [0.5393,0.5868] [0.3260,0.3522] [0.5385,0.6012] [0.2109,0.2222] [0.2874,0.3083]
0.9 [0.2514,0.2578] [0.3856,0.3947] [0.3960,0.4111] [0.3100,0.3158] [0.7641,0.7745] [0.5386,0.5463] [0.3231,0.3273] [0.5317,0.5415] [0.2076,0.2094] [0.2817,0.2850]
1 0.2519 0.3825 0.3974 0.3107 0.7641 0.5383 0.3217 0.5282 0.2060 0.2789
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These bounds are introduced in (8) and the CSW is evaluated. This CSW for different Į in [0,1] is presented in Table 1. After fixing the input and output prices for all inputs and outputs, the efficiencies of DMUs are evaluated by (9). The interval efficiencies by the CSW are shown in Table 2 for different Į in [0,1]. 5. Conclusion The calculation of DEA scores requires a linear program per DMU and generates an individual set of endogenous weights for each performance dimension. Given a large number of DMUs in real applications, the computational and conceptual complexities are considerable with weights that are potentially zero-valued or incommensurable across units. To overcome this problem, a procedure for finding a CSW in fuzzy CCR model is suggested. In contrast to the other methods, the presented procedure is very useful and applicable. The proposed algorithm reduces the computational complexities and costs as well as overcoming pitfalls in the DEA including the zero-value and differing weights and multiple solutions. References 1. A. Charnes, W.W., Cooper, and E.L. Rhodes, Measuring the efficiency of decision making units, Eur. J. Operat. Res, 2(6), 429(1978). 2. R.G. Thompson, F. Singleton, R. Thrall, and B. Smith, Comparative site evaluations for locating a high-energy physics lab in Texas. Interfaces, 16, 35(1986). 3. M. Khalili, A.S. Camanho, M.C.A.S. Portela and M.R. Alirezaee, The measurement of relative efficiency using data envelopment analysis with assurance regions that link inputs and outputs. Eur. J. Operat. Res, 203 (3), 761(2010). 4. G.R. Jahanshahloo, F. Hosseinzadeh Lotfi, M. Khanmohammadi, M. Kazemimanesh, and V. Rezaie, Ranking of units by positive ideal DMU with common weights. Expert Syst Appl. 37 (12), 7483(2010). 5. F.H.F. Liu and H.H. Peng, Ranking of DMUs on the DEA frontier with common weights. Comput Oper Res, 35 (5), 1624 (2008). 6. S. Saati, Determining a common set of weights in DEA by solving a linear programming. J Ind Eng Int, 4 (6), 5(2008). 7. S. Saati and A. Memariani, Reducing weight flexibility in fuzzy DEA, Appl Math Comput, 161(2), 611(2005). 8. A. Hatami-Marbini, A. Emrouznejad and M. Tavana, A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making. Eur. J. Operat. Res, 214(3), 457(2011). 9. R.E., Moore, B.B. Kearfortt, and M.J. Cloud, Introduction to interval analysis, SIAM, Philadelphia, pp. 11(2009).
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