Multi-Criteria Project Selection Using an Extended VIKOR Method with Interval Type-2 Fuzzy Sets

• Published in: International journal of information technology & decision making Vol. 14; no. 5; pp. 993 - 1016
• Main Authors: Ghorabaee, Mehdi Keshavarz, Amiri, Maghsoud, Sadaghiani, Jamshid Salehi, Zavadskas, Edmundas Kazimieras
• Format: Journal Article
• Language: English
• Published: Singapore World Scientific Publishing Company 01.09.2015; World Scientific Publishing Co. Pte., Ltd
• Subjects: Criteria; Decision analysis; Decision making; Economic models; Fuzzy; Fuzzy logic; Fuzzy set theory; Fuzzy sets; Goal programming; Intervals; Multiple criterion; Stability; Stability analysis; Stability criteria; Viability; VIKOR method; interval type-2 fuzzy sets; multi-criteria group decision making; project selection
• ISSN: 0219-6220; 1793-6845
• DOI: 10.1142/S0219622015500212

Project selection can be a real problem of the multi-criteria group decision making if a group of decision makers express their preferences depending on the nature of the alternatives and different criteria with respect to their knowledge about them. The purpose of the project selection process is to analyze project viability and to approve or reject project proposals based on established criteria. Such decisions are often complex, because they require the identification, consideration and analysis of many tangible and intangible factors. This paper presents a multi-criteria group decision-making approach for project selection problem in the type-2 fuzzy environment. The proposed method is an extended version of Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method with interval type-2 fuzzy numbers; it is called type-2 fuzzy VIKOR (T2F-VIKOR). A stepwise procedure is used for ranking and evaluating the alternatives in the developed method, and the best solution is selected considering both the beneficial and nonbeneficial criteria. An illustrative example is presented to show the applicability of the proposed approach in the project selection problems, and the results are analyzed. The results are compared with some existing methods to show the validity of the extended method. We also utilize six sets of criteria weights for analyzing the stability of the proposed method. These analyses show that the obtained results of the proposed method are relatively consistent with other methods and have good stability in different criteria weights.