Interval-valued intuitionistic fuzzy multiple attribute decision making based on nonlinear programming methodology and TOPSIS method

被引：113
|
作者：
Zeng, Shouzhen [1 ,3 ]
Chen, Shyi-Ming [2 ]
Fan, Kang-Yun [2 ]
机构：
[1] Ningbo Univ, Sch Business, Ningbo 315211, Zhejiang, Peoples R China
[2] Natl Taiwan Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan
[3] Fudan Univ, Sch Management, Shanghai 200433, Peoples R China
来源：
INFORMATION SCIENCES | 2020年 / 506卷
基金：
中国博士后科学基金;
关键词：
IVIFSs; IVIFVs; MADM; Nonlinear programming methodology; TOPSIS method; LOGICAL RELATIONSHIP GROUPS; SCORE FUNCTION; AGGREGATION OPERATORS; TIME-SERIES;
D O I：
10.1016/j.ins.2019.08.027
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 propose a new multiple attribute decision making (MADM) method based on the nonlinear programming (NLP) methodology, the TOPSIS method and interval-valued intuitionistic fuzzy values (IVIFVs). The evaluating values of the alternatives with respect to attributes and the attributes' weights are represented by IVIFVs. The NLP methodology is applied to get the optimal attributes' weights. The proposed MADM method can overcome the drawbacks of the existing MADM methods to deal with MADM problems using IVIFVs. (C) 2019 Elsevier Inc. All rights reserved.
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页码：424 / 442
页数：19
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