Possibility Method for Triangular Intuitionistic Fuzzy Multi-attribute Group Decision Making with Incomplete Weight Information

被引:0
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作者
Shu-Ping Wan
Jiu-Ying Dong
机构
[1] Jiangxi University of Finance and Economics,College of Information Technology
[2] Jiangxi University of Finance and Economics,Jiangxi Key Laboratory of Data and Knowledge Engineering
[3] Jiangxi University of Finance and Economics,College of Statistics
关键词
Multi-attribute group decision making; Triangular intuitionistic fuzzy number; Possibility mean; Possibility variance; Possibility standard deviation;
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学科分类号
摘要
Triangular intuitionistic fuzzy numbers (TIFNs) are a special kind of intuitionistic fuzzy sets (IFSs) on a real number set. TIFNs are useful to deal with ill-known quantities in decision data and decision making problems themselves. The purpose of this paper is on developing a new ranking method of TIFNs and application to multiattribute group decision making (MAGDM) problems in which the attribute values are expressed with TIFNs and the information on attribute weights is incomplete. The weighted average operator of TIFNs is defined, the concepts of the possibility mean, variance of TIFNs as well as standard deviation are introduced. Hereby two new ranking indices considering the risk attitude of decision maker are developed to rank TIFNs. In the proposed group decision method, the collective overall attribute values of alternatives are obtained by using the weighted average operator of TIFNs We construct the multi-objective programming of maximizing the ranking indices of membership and non-membership functions on alternative’s collective overall attribute values, which is transformed into a single linear programming model by using the membership function based weighted sum approach. Thus, the ranking indices of membership and non-membership functions for the alternatives are derived, which are used to rank the alternatives. A personnel selection example is analyzed to demonstrate the applicability, universality and flexibility of the proposed models and method.
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页码:65 / 79
页数:14
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