Intuitionistic Trapezoidal Fuzzy Multiple Criteria Group Decision Making Method Based on Binary Relation | Zendy

Liyuan Zhang | Zendy; Tao Li | Zendy; Xuanhua Xu | Zendy

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Intuitionistic Trapezoidal Fuzzy Multiple Criteria Group Decision Making Method Based on Binary Relation

Author(s) -

Liyuan Zhang,

Tao Li,

Xuanhua Xu

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/348928

Subject(s) - mathematics , measure (data warehouse) , similarity (geometry) , relation (database) , group (periodic table) , binary number , rank (graph theory) , fuzzy set , similarity measure , set (abstract data type) , group decision making , fuzzy logic , mathematical optimization , algorithm , data mining , artificial intelligence , computer science , combinatorics , arithmetic , chemistry , organic chemistry , political science , law , image (mathematics) , programming language

The aim of this paper is to develop a methodology for intuitionistic trapezoidal fuzzy multiple criteria group decision making problems based on binary relation. Firstly, the similarity measure between two vectors based on binary relation is defined, which can be utilized to aggregate preference information. Some desirable properties of the similarity measure based on fuzzy binary relation are also studied. Then, a methodology for fuzzy multiple criteria group decision making is proposed, in which the criteria values are in the terms of intuitionistic trapezoidal fuzzy numbers (ITFNs). Simple and exact formulas are also proposed to determine the vector of the aggregation and group set. According to the weighted expected values of group set, it is easy to rank the alternatives and select the best one. Finally, we apply the proposed method and the Cosine similarity measure method to a numerical example; the numerical results show that our method is effective and practical

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