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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Luo Chunlin & Tian Xin & Wan Shuping, 2015. "Heavy OWA Operator of Trapezoidal Intuitionistic Fuzzy Numbers and its Application to Multi-Attribute Decision Making," Journal of Systems Science and Information, De Gruyter, vol. 3(1), pages 86-96, February.
    • Handle: RePEc:bpj:jossai:v:3:y:2015:i:1:p:86-96:n:9
    DOI: 10.1515/JSSI-2015-0086
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