1
School of Industrial Engineering , Iran University of Science and Technology
2
Industrial Engineering Department, Faculty of Engineering, Shahed University
Abstract
Select an appropriate project is a main key for contractors to increase their profits. In practice, in this area the uncertainty and imprecise of the involved parameters is so high. Therefore, considering fuzzy sets theory to deal with uncertainly is more appreciate. The aim of this paper is present a multi-criteria group decision-making model under an intuitionistic fuzzy set environment. Hence, the weight of each decision maker and each criterion are considered different. Indeed, decision makers' weights are determined based on a novel intuitionistic fuzzy index, and criteria’ weights are specified by proposed method according to the concept of closer to ideal solution and farther from negative ideal solution. Then, the potential projects are ranked based on new intuitionistic fuzzy relative closeness coefficient. Thus, the proposed intuitionistic fuzzy group decision-making model is applied in an illustrative example about construction project selection from the recent literature. Finally, the ranking results are compared with a fuzzy TOPSIS method to indicate the applicability and efficiency of the proposed model.
Gitinavard, H., & Mousavi, S. (2015). Evaluating Construction Projects by a New Group Decision-Making Model Based on Intuitionistic Fuzzy Logic Concepts. International Journal of Engineering, 28(9), 1312-1319.
MLA
H. Gitinavard; S.M. Mousavi. "Evaluating Construction Projects by a New Group Decision-Making Model Based on Intuitionistic Fuzzy Logic Concepts". International Journal of Engineering, 28, 9, 2015, 1312-1319.
HARVARD
Gitinavard, H., Mousavi, S. (2015). 'Evaluating Construction Projects by a New Group Decision-Making Model Based on Intuitionistic Fuzzy Logic Concepts', International Journal of Engineering, 28(9), pp. 1312-1319.
VANCOUVER
Gitinavard, H., Mousavi, S. Evaluating Construction Projects by a New Group Decision-Making Model Based on Intuitionistic Fuzzy Logic Concepts. International Journal of Engineering, 2015; 28(9): 1312-1319.
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