A NEW METHOD OF ASSESSMENT BASED ON FUZZY RANKING AND AGGREGATED WEIGHTS (AFRAW) FOR MCDM PROBLEMS UNDER TYPE-2 FUZZY ENVIRONMENT

Mehdi KESHAVARZ Ghorabaee (), Edmundas Kazimieras Zavadskas (), Maghsoud Amiri () and Jurgita Antucheviciene ()
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Mehdi KESHAVARZ Ghorabaee: Department of Industrial Management, Faculty of Management and Accounting, AllamehTabataba’i University, Tehran, Iran
Edmundas Kazimieras Zavadskas: Department of Construction Technology and Management, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Lithuania
Maghsoud Amiri: Department of Industrial Management, Faculty of Management and Accounting,AllamehTabataba’i University, Tehran, Iran
Jurgita Antucheviciene: Department of Construction Technology and Management, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Lithuania

ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, 2016, vol. 50, issue 1, 39-68

Abstract: Fuzzy multi-criteria decision-making (MCDM) methods and problems have increasingly been considered in the past years. Type-1 fuzzy sets are usually used by decision-makers (DMs) to express their evaluations in the process of decision-making. Interval type-2 fuzzy sets (IT2FSs), which are extensions of type-1 fuzzy sets, have more degrees of flexibility in modeling of uncertainty. In this research, a new ranking method to calculate the ranking values of interval type-2 fuzzy sets is proposed. A comparison is performed to show the efficiency of this ranking method. Using the proposed ranking method and the arithmetic operations of IT2FSs, a new method of Assessment based on Fuzzy Ranking and Aggregated Weights (AFRAW)is developed for multi-criteria group decision-making. To obtain more realistic and practical weights for the criteria, the subjective weights expressed by DMs and objective weights calculated based on a deviation-based method are combined, and the aggregated weights are used in the proposed method. A numerical example related to assessment of suppliers in a supply chain and selecting the best one is used to illustrate the procedure of the proposed method. Moreover, a comparison and a sensitivity analysis are performed in this study. The results of these analyses show the validity and stability of the proposed method.

Keywords: MCDM; interval type-2 fuzzy sets; fuzzy ranking method; multi-criteria group decision-making; AFRAW. (search for similar items in EconPapers)
JEL-codes: C02 C44 C61 C63 L6 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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