An interactive method for dynamic intuitionistic fuzzy multi-attribute group decision making

被引:118
|
作者
Su, Zhi-xin [1 ,2 ]
Chen, Ming-yuan [2 ]
Xia, Guo-ping [1 ]
Wang, Li [1 ]
机构
[1] Beihang Univ, Sch Econ & Management, Beijing 100191, Peoples R China
[2] Concordia Univ, Dept Mech & Ind Engn, Montreal, PQ H3G 1M8, Canada
基金
中国国家自然科学基金;
关键词
Dynamic intuitionistic fuzzy multi-attribute group decision making (DIF-MAGDM); Intuitionistic fuzzy numbers (IFNs); Aggregation operators; Intuitionistic fuzzy TOPSIS method; Consensus; GROUP-PREFERENCE AGGREGATION; OWA OPERATORS; VAGUE SETS; WEIGHTS; INFORMATION; MULTIPERSON; ENVIRONMENT; MODELS;
D O I
10.1016/j.eswa.2011.06.022
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper investigates the dynamic intuitionistic fuzzy multi-attribute group decision making (DIF-MAGDM) problems, in which all the attribute values provided by multiple decision makers (DMs) at different periods take the form of intuitionistic fuzzy numbers (IFNs), and develops an interactive method to solve the DIF-MAGDM problems. The developed method first aggregates the individual intuitionistic fuzzy decision matrices at different periods into an individual collective intuitionistic fuzzy decision matrix for each decision maker by using the dynamic intuitionistic fuzzy weighted averaging (DIFWA) operator, and then employs intuitionistic fuzzy TOPSIS method to calculate the individual relative closeness coefficient of each alternative for each decision maker and obtain the individual ranking of alternatives. After doing so, the method utilizes the hybrid weighted averaging (HWA) operator to aggregate all the individual relative closeness coefficients into the collective relative closeness coefficient of each alternative and obtain the aggregate ranking of alternatives, by which the optimal alternative can be selected. In addition, the spearman correlation coefficient for both the aggregate ranking and individual ranking of alternatives is calculated to measure the consensus level of the group preferences. Finally, a numerical example is used to illustrate the developed method. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:15286 / 15295
页数:10
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