Novel Cross-Entropy Based on Multi-attribute Group Decision-Making with Unknown Experts' Weights Under Interval-Valued Intuitionistic Fuzzy Environment

被引：7

作者：

Li, Yonghong ^{[1
]}

Cheng, Yali ^{[1
]}

Mou, Qiong ^{[1
]}

Xian, Sidong ^{[1
]}

机构：

[1] Chongqing Univ Posts & Telecommun, Key Lab Intelligent Anal & Decis Complex Syst, Sch Sci, Chongqing 400065, Peoples R China

来源：

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS | 2020年 / 13卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Interval-valued intuitionistic fuzzy set; Experts' weights; Cross-entropy; Multi-attribute group decision-making; DIVERGENCE; MAGDM;

D O I：

10.2991/ijcis.d.200817.001

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 studies the multi-attribute group decision-making problems with unknown experts' weights under interval-valued intuitionistic fuzzy environment. First, in order to provide more flexibilities for decision-makers in actual decision-making problems, a novel cross-entropy measure with parameter of interval-valued intuitionistic fuzzy set (IVIFS) based on J-divergence is proposed. The novel cross-entropy measure can obtain more flexible and practical optimal ranking results by adjusting the parameter. Then, by using the designed cross-entropy measure, two models are established to obtain experts' weights, which consider the influence of experts' experience and professional knowledge on experts' weights. Finally, two examples are provided to illustrate the effectiveness and applicability of optimizing the group decision-making approach. (C) 2020 The Authors. Published by Atlantis Press B.V.

引用

页码：1295 / 1304

页数：10

共 41 条

[1] INTERVAL VALUED INTUITIONISTIC FUZZY-SETS [J].