Multiple attribute decision making using improved intuitionistic fuzzy weighted geometric operators of intuitionistic fuzzy values

被引：67

作者：

Zou, Xin-Yao ^{[1
]}

Chen, Shyi-Ming ^{[2
]}

Fan, Kang-Yun ^{[2
]}

机构：

[1] Guangdong AIB Polytech Coll, Off Sci Res & Ind Serv, Guangzhou, Peoples R China

[2] Natl Taiwan Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan

来源：

INFORMATION SCIENCES | 2020年 / 535卷

关键词：

Intuitionistic fuzzy geometric operators; IFSs; IFVs; MADM; IIFWG operator; NONLINEAR-PROGRAMMING METHODOLOGY; AGGREGATION OPERATORS; SIMILARITY MEASURES; TIME-SERIES; SETS;

D O I：

10.1016/j.ins.2020.05.011

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we develop a novel multiple attribute decision making (MADM) method using the improved intuitionistic fuzzy weighted geometric (IIFWG) operator of intuitionistic fuzzy values (IFVs) proposed in this paper. First, we develop the IIFWG operator of IFVs to conquer the weak points of the existing operators of IFVs, where they have the drawbacks that their aggregated values are indeterminate in some situations. Based on the proposed IIFWG operator of IFVs, we present a MADM method to overcome the weak points of the existing MADM methods, which have the shortcomings that they obtain unreasonable ranking orders (ROs) of alternatives or they cannot discriminate the ROs of alternatives in some circumstances. (C) 2020 Elsevier Inc. All rights reserved.

引用

页码：242 / 253

页数：12

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