Heavy OWA Operator of Trapezoidal Intuitionistic Fuzzy Numbers and its Application to Multi-Attribute Decision Making

Luo Chunlin (), Tian Xin () and Wan Shuping ()
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Luo Chunlin: School of Management, University of Chinese Academy Sciences, Beijing, 100190, China
Tian Xin: Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, 100190, China
Wan Shuping: School of Management, University of Chinese Academy Sciences, Beijing, 100190, China

Journal of Systems Science and Information, 2015, vol. 3, issue 1, 86-96

Abstract: Heavy ordered weighted averaging (OWA) operator is important for characterizing the decision maker’s attitudinal character in multi-attribute decision making (MADM) problem with part or total ignorance. This paper develops a new method based on heavy OWA operator to solve the MADM problem in which the attributes are characterized by some trapezoidal intuitionistic fuzzy numbers (TrIFNs). TrIFN, as a special kind of intuitionistic fuzzy set defined on the real numbers, is useful for characterizing the ill-known quantity in reality. Firstly, the operation laws and the cut sets concept for TrIFNs are introduced. Then the authors define the membership and non-membership average indexes. A new ranking method is developed on the basis of the two indexes. In the proposed decision model, the multi-attribute TrIFN values of the candidates are aggregated by the Heavy OWA operator, and ranked by their membership and non-membership average indexes. Lastly, the authors illustrate the proposed method by a numerical example which implies the practicality and effectiveness of the method.

Keywords: Heavy OWA; trapezoidal intuitionistic fuzzy number; MADM; ranking (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:3:y:2015:i:1:p:86-96:n:9

DOI: 10.1515/JSSI-2015-0086

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