Correlation coefficient of interval-valued intuitionistic fuzzy sets and its application to multiple attribute group decision making problems

被引:212
|
作者
Park, Dong Gun [2 ]
Kwun, Young Chel [2 ]
Park, Jin Han [1 ]
Park, Il Young [1 ]
机构
[1] Pukyong Natl Univ, Div Math Sci, Pusan 608737, South Korea
[2] Dong A Univ, Dept Math, Pusan 604714, South Korea
关键词
Multiple attribute group decision making (MAGDM); Interval-valued intuitionistic fuzzy decision matrix; Interval-valued intuitionistic fuzzy number; Correlation coefficient; Interval-valued intuitionistic fuzzy weighted geometric (IIFWG) operator; Interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator; OPERATORS;
D O I
10.1016/j.mcm.2009.06.010
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we investigate the group decision making problems in which all the information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFN), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and then we use the obtained attribute weights and the interval-valued intuitionistic fuzzy weighted geometric (IIFWG) operator to fuse the interval-valued intuitionistic fuzzy information in the collective interval-valued intuitionistic fuzzy decision matrix to get the overall interval-valued intuitionistic fuzzy values of alternatives, and then rank the alternatives according to the correlation coefficients between IVIFNs and select the most desirable one(s). Finally, a numerical example is used to illustrate the applicability of the proposed approach. (c) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1279 / 1293
页数:15
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