Construction Project Selection using AHP and ELECTRE 1
1,2
Majid Mojahed, 2Rosnah bt Mohd Yusuff Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, Malaysia 1
[email protected] ,
[email protected]
ABSTRACT A project is a temporary endeavor undertaken to create a unique product, service or result. Selecting projects is often a difficult task. Usually there are more than one dimension for measuring the impact of each project and especially when there is more than one decision maker. The criteria being considered always vary from one contractor to another. Some may only consider the revenue and value of project, whilst some may focus on its financial of owner, knowledge of supervisor and so on. In this paper, it is used different criteria such as qualitative and quantitative that all of them are positive. Opinions from 10 contractors involved in telecommunication construction projects were used to identify the main criteria for project selection and finally six criteria have been determined as the main criteria by them. Analytical Hierarchy Process (AHP) was used to compare the relative importance of the criteria and weights given to each criterion. By using ELECTRE, three projects were chosen and ranked based on the six criteria identified. Even after, when at least one of Projects’ grades was placed in the same with another, AHP method will rank them in different grades. Finally P3 was determined as the best Project and then P2 and P1 (in equal level) were put in second grade by ELECTRE method, P3 > (P2 =P1). Afterward, AHP specified that P2 is preferred to P1. So the result is: P3 > P2 >P1.
Keywords: Project Selection, Analytical Hierarchy Process (AHP), Elimination et choice Translating reality (ELECTRE).
INTRODUCTION Project selection and project evaluation involve decisions that are critical to the profitability, growth and survival of project management organizations in the increasingly competitive global scenario. Such decisions are often complex, because they require identification, consideration and analysis of many tangible and intangible factors [1]. The criteria were set up into Intrinsic (parts of the real nature of project) and Extrinsic (not belonging naturally to project) groups [2]. Some criteria were introduced in IS and R&D fields [3, 4]. Other methods for applying Project selection are, Fuzzy logic for R&D project selection and scheduling, Goal programming (GP) method for a project planning problem [5], A practical tool of incorporating random Fuzzy uncertainty into project selection [6] and TOPSIS and AHP methods for ranking projects by using seven criteria that four of them were engineering economy techniques [7]. The main objective of this study is determining the best construction Project and ranking them. Another objective is to specify the essential criteria of construction projects in order to rank them in North Khorasan Telecommunication – Iran. Results of the study will be used by constructors in order to allow them to select the best project and also may be used by the authorities, managers and decision makers to identify contractors’ viewpoints in all construction projects which are one of the main project problems.
ELECTRE and AHP methods Multi criteria decision making (MCDM) is one of the most widely used decision methodologies in the sciences, business, government and engineering worlds. MCDM methods can help to improve the quality of decisions by making the decision-making process more explicit, rational, and efficient [8]. Some applications of MCDM in engineering include the use on flexible manufacturing systems [9], layout design [10], integrated manufacturing systems [11], and the evaluation of technology investment decisions [12].
Many methods have been proposed to analyze the data of a decision matrix and rank the alternatives. Often times different MCDM methods may yield different answers to exactly the same problem [13] and also some of the methods use additive formulas to compute the final priorities of the alternatives. The ELECTRE evaluation method is widely recognized for high-performance policy analysis involving both qualitative and quantitative criteria. However, a critical advantage of this evaluation method is its capacity to point the exact needs of a decision maker and suggest an appropriate evaluation approach. The discordance indices of modified ELECTRE evaluation method are used to explain the significance of modified evaluation standards [14]. The ELECTRE method is a well known method, especially in Europe too. It has been widely used in civil and environmental engineering [15]. Applications include the assessment of complex civil engineering projects, selection of highway designs, site selection for the disposal of nuclear waste, water resources planning [16] and waste water [17] or solid waste management [18] and etc. ELECTRE was conceived by [19] in response to deficiencies of existing decision making solution methods. ELECTRE is more than just a solution method; it is a Philosophy of decision aid - the philosophy is discussed at length by [19]. However, for this paper we specifically concentrate on what is referred to as ELECTRE. ELECTRE has evolved through a number of versions (I, II, II, IV, V, IS, A); all are based on the same fundamental concepts but are operationally somewhat different [20]. The ELECTRE method involves nine steps to help decision makers as followed: Step 1: Calculate the normalized decision matrix. =
;
i =1, 2… m ; j=1, 2… n,
Step 2: Calculate the weighted normalized decision matrix. , We assumed that “W” is a diagonal matrix (n⨉n) which values of its main diameter are W and the rest values are zero.
W=
w1
0
0
… 0
0
0
w2
0
… 0
0
0
0
w3
… 0
0
.
.
.
.
.
0
0
0
… 0
0
0
0
0
… 0
wn
Step 3: Determine the concordance and discordance set. = {J |
}
;
(
=1, 2, 3, … m;
)
,
When this condition is true then we put “1” in its place otherwise we put “0”. We will also apply for discordance set as followed:
; It is obvious that
(
=1, 2, 3, … m;
)
,
are opposite then places of “0” belong to
.
Step 4: Calculate the concordance matrix.
In this matrix (I) is So each element of matrix includes sum of element(s) W, that they depend to will be between: Therefore, each elements of Step 5: Calculate the discordance matrix. During computing matrix of NI, it is necessary that ( computed as follow:
=1, 2, 3, … m;
.
) , so each elements of matrix will be
, Step 6: Determine the concordance dominance matrix. Dimension of matrix F and matrix I (in step 4) are the same but for finding matrix F, it is needed to compute threshold amount ( ) as follow: =
;
(m is dimension of matrix),
Matrix F can be calculated by using matrix I if each corresponding elements of matrix I, are divided to I (Threshold amount of this step).
, , The above inequalities mean that if each element of matrix I, is greater than or equal to , then “1” would be set in matrix F (corresponding element). Step 7: Determine the discordance dominance matrix. So we calculate matrix of G.
N =
,
(m is dimension of matrix),
Matrix G can be calculated by using matrix NI, if each corresponding elements of matrix NI, are divided to (Threshold amount of this step).
, Also the above inequalities mean that if each element of matrix NI, is less than or equal to in matrix G (corresponding element). Step 8: Determine the aggregate dominance matrix. We also compute matrix H. “P is means Project”
, then “1” would be set
So matrix H is performed by multiplying corresponding elements of F and G. Step 9: Eliminate the less favorable alternative and rank them. Finally, we must scan the columns of matrix H, each column that has the least amount of number “1” should be chosen as the best one and it will be followed by others. Analytic Hierarchy Process (AHP) is one widely used multi criteria decision making method introduced by [20] and it resolves decision making problems by structuring each problem into a hierarchy with different levels of criteria. In other word, AHP structures a decision problem into a hierarchy and evaluate multi criteria tangible and intangible factors systematically. AHP also has been applied in numerous fields [21, 22, 23] including many software selection decisions.
The AHP method involves four steps to solve a decision problem [23, 24, 25]: Steps of AHP method: Step 1: Structuring the decision problem. Structure the hierarchy from the top (goal) through the intermediate levels (criteria, sub-sequent levels depend on) to the lowest level which usually contains the list of alternatives. Step 2: Creating pairwise comparison Matrix. After constructing AHP model, the priorities should be done. Weights are assigned to each criterion and sub criterion. These weights are assigned through a process of pairwise comparison. In pairwise comparison, each objective is compared at a peer level in terms of importance. In this time, a set of pair-wise comparison matrices (size n ⨉ n) for each of the lower levels with one matrix for each element in the level immediately above by using the relative scale measurement shown in Table 1 is constructed. The pairwise comparisons are done in terms of which element dominates the other. Step 3: Determining normalized weights. So By using each pairwise comparison Matrices, weight of each rows was computed by matrix of “W”. i=1, 2,.. n ; j=1,2,…m
)/n
i=1, 2,.. n (denominator must be size of matrix)
Step 4: Synthesize the priorities. The final step is to synthesize the solution for the decision problem in order to obtain the set of priorities for alternatives. After computing the weight of Alternatives in respect to sub criteria and then sub criteria in respect to criteria and also criteria in respect to goal from Step 3 (in the level immediately above), they are aggregated to produce composite weights which used to evaluate decision alternatives.
METHODOLOGY The following phases have been designed to address the research methodology: Phase 1: The first phase of this paper is designed in order to select and consider suitable criteria and Projects in one of a sector of Telecommunication’s Company respectively. The way of data collection that is applied for this phase is interview, voting and questionnaire. By using Comparison Matrix, weights of criteria will be computed. After computing weights of criteria, specifying of Consistency will be executed. If the Consistency is less than 0.1, then we use ELECTRE method for pre-ranking Projects. This phase is important because it provides the knowledge platform and pre-selecting Projects for next phase. Phase 2: The applied methodology for this phase is based on output of previous phase and the method used is AHP. In this phase, after identifying the level of Projects, we apply AHP method when at least one of Projects’ grades was placed in the same with another. In this way, specifying of Consistency will be executed too. In both of phases, if Consistency of data is less than 0.1, revision of pairwise comparison must be done. At the end of this phase, all of Projects which had been considered will be sorted in different level.
Start
Interview for finding
Considering some
Selecting suitable criteria
Projects Questionnaire
Computing weights of criteria by using Comparison Matrix Revision of pairwise comparison N
Is Consistency true?
Ye
Using ELECTRE method for ranking Projects
Using AHP method for ranking the Projects in the same grade
No
Are Projects in the different grade?
Yes Yes
Is Consistency true?
Determining Projects’ rank and selecting the best one No
Revision of pairwise comparison
Figure 1
End
In this paper, data was collected by interview method (specifying criteria), Voting (selecting essential criteria) and questionnaire (comparing criteria). So this research has collected data from a relatively whole group of respondent’s points of view who are the contractors. The gathered data of this research considers the Criteria of construction project selection in Telecommunication of Iran. In this study, opinions from 10 contractors involved in construction projects were used to identify the main criteria for project selection. In interview we found 15 Criteria which six of them got more score in voting. Afterward, the Criteria that had gotten more than five score were selected.
Table 1:Criteria and their definition
List of criteria
Definition
Insurance cover
To solve most of unpredictable problems in projects.
Comfort of route
It shows safety of route where the project is implemented.
Material availability
To find amount of raw materials that contractors can provide from the place that project implement.
Experience of owner [3]
Doing several similar projects by owner.
Financial of owner
It causes enough money to be given to the contractor.
Benefit [2]
Subtraction between of contractor's amount of receipt and all costs.
Unrealistic imposed order by owner
The owner’s unrealistic imposed order cause to occur harms to project.
A promising future
The owner promises to give some opportunity to contractor in future.
Political impact in area
Some areas have political pressures that it will cause regional unrest.
Management attitude [3]
The owner’s behavior and deal with contractor.
Delay and penalty
The crimes and faults that may be imposed to the contractors.
Problem of regulations
Instructions must be clear and comprehensive.
Having management and control project knowledge
Having this knowledge can be better run successful projects.
The owner policies and regulations
The owner’s policies may cause to prevent some harms of project.
Being familiar with the area or being domestic
How much a contractor knows about the place where the project will do there.
After specifying relative criteria and also considering three Projects as alternatives, computing the weights of criteria were started by using comparison matrix. In this research scale of (1-5) has been done as follow: Table 2: scale of (1-5)
Intensity of importance
Definition
1
Equal importance
2
Moderate importance
3
Strong importance
4
Very strong
5
Extreme importance
Data was gathered from ten Contractors’ point of view in Telecommunication Company. Following steps will be shown the way of solving an application problem in ELECTRE method and finally with AHP method it will rank the result of ELECTRE that some Projects were in the same level.
NUMERICAL EXAMPLE In interview we found 15 Criteria which six of them got more score. By voting six Criteria got more than five score so they were selected. Finally six main Criteria were selected and here are criteria that have been mentioned above: Computing the weights of criteria has been done by using comparison matrix. Meanwhile, Data was gathered from ten Contractors’ point of view in Telecommunication Company. After specifying relative criteria and also considering three of popular projects as alternatives, computing the weights of criteria were started as followed:
Table 3
Criteria
C1
C2
C3
C4
C5
C6
weights
C1
1.00
2.00
3.00
3.00
2.00
0.25
0.179
C2
0.50
1.00
2.00
2.00
1.00
0.20
0.107
C3
0.33
0.50
1.00
1.00
0.50
0.17
0.061
C4
0.33
0.50
1.00
1.00
0.50
0.17
0.061
C5
0.50
1.00
2.00
2.00
1.00
0.20
0.107
C6
4.00
5.00
6.00
6.00
5.00
1.00
0.484
15.00
10.00
1.98
Total 6.67 10.00 15.00 W= {0.179, 0.107, 0.061, 0.061, 0.107, 0.484}
The above table has been completed by ten expert’s point of view in one of sector in Telecommunication Company. Each contractor fills it up by using table 1 separately and then by computing average and after that round off, table 3 has been completed. For example number 2 in column 2 and row 1 shows that C1 is moderate importance than C2 and also number 3 in column 4 and the same row indicates C1 is strong importance than C4.The consistency Index is calculated 0.015 that is less than 0.1 so indicates sufficient consistency. Following steps will be shown the way of solving an application problem in ELECTRE method. Step 1: Table 4
C1 5 5 3
C2 3 8 5
C3 4 8 6
C4 6 7 7
C5 6 8 7
C6 5 4 6
C1
C2
C3
C4
C5
C6
P1
0.117
0.032
0.023
0.032
0.053
0.276
P2
0.117
0.032
0.023
0.032
0.053
0.276
P3
0.070
0.054
0.034
0.037
0.061
0.331
P1 P2 P3 Step 2: Table 5
Step 3:
Table 6
S1,2 S1,3
J=1 1 1
J=2 1 -
J=3 1 -
J=4 1 -
J=5 1 -
J=6 1 -
D1,2 D1,3
0 2,3,4,5,6
J=1 1 1
J=2 1 -
J=3 1 -
J=4 1 -
J=5 1 -
J=6 1 -
D2,1 D2,3
0 2,3,4,5,6
J=1 -
J=2 1 1
J=3 1 1
J=4 1 1
J=5 1 1
J=6 1 1
D3,1 D3,2
1 1
1.000 0.821
0.179 0.179 -
Table 7
S2,1 S2,3
Table 8
S3,1 S3,2 Step 4:
Table 9
1.000 0.821 Step 5:
Table 10
0 0.775913 0 0.775913 0.775913 0.775913 -
Step 6:
Table 11
1
1 -
0 0
1
1
-
1
1 -
0 0
0
0
-
Step 7:
Table 12
Step 8: We also compute matrix of H. “P is means project” Table 13
Projects P1 P2 P3
P1 1 0
P2 1 0
P3 0 0 -
Step 9: Finally in ELECTRE method, the best Project will be P3 and then P2 and P1 (in equal level) P3 > (P2 =P1). By using AHP, we solve this problem and determined that P3 also is the first and P2 will be preferred to P1. So the result is: P3 > P2 >P1.
CONCLUSION AND RECOMMENDATIONS To specify the best project, contractors usually compare some criteria of projects, but they not enough. The criteria being considered always vary from one contractor to another. In this paper it is also used different criteria such as qualitative and quantitative that all of them are positive. The weights of Criteria were computed in table 3. These data has been gathered from 10 construction’s contractors in Telecommunication Company of North Khorasan – Iran in order to identify degree of their importance and finally their weights were specified in it. This table shows five essential criteria that the most important criterion is C6 (Benefit) and the others are in order as followed: C1 (Insurance cover), C2 (Comfort of route), C5 (Financial of owner), C3 (Material availability) and C4 (Experience of owner). These criteria help to contractors for ranking projects and selecting the best project and also help to owners and decision makers for monitoring and performing contractors’ point of view. In addition, the owners and decision makers can detect some major criteria to do more attention. Authors suggest detecting the relation between these criteria which have been informed in this paper. If these relations are specified then the table 3 will be close to the truth presumably.
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