Fuzzy multi-criteria acceptability analysis: A new approach to multi-criteria decision analysis under fuzzy environment

被引：31

作者：

Yatsalo, Boris ^{[1
]}

Korobov, Alexander ^{[1
]}

Martinez, L. ^{[2
,3
]}

机构：

[1] Natl Res Nucl Univ MEPHI LATE NRNU MEPHI, Inst Cybernet Intelligent Syst, Dept Informat Syst, Moscow, Russia

[2] Univ Jaen, Dept Comp Sci, Jaen 23071, Spain

[3] Wuhan Univ Technol, Sch Management, Wuhan 430070, Peoples R China

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2017年 / 84卷

关键词：

Multi-criteria decision analysis; Uncertainty; Fuzzy sets; Ranking fuzzy numbers; MAVT; REASONABLE PROPERTIES; MAKING TECHNIQUES; RANKING; NUMBERS;

D O I：

10.1016/j.eswa.2017.05.005

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Uncertainty is one of the main difficulties that increases the complexity of multi-criteria decision analysis (MCDA) problems, and often uncertainty cannot be managed by probabilistic models. In such cases, the use of fuzzy methods has been successfully applied to multi-criteria decision methods in which the ranking of fuzzy quantities is crucial for the decision analysis. This paper aims to introduce a new approach to MCDA problems defined under fuzzy contexts that implements the concept of acceptability analysis, Fuzzy Multi-Criteria Acceptability Analysis (FMAA), based on the Fuzzy Rank Acceptability Analysis (FRAA), that provides a ranking and a confidence degree about the ranking of fuzzy quantities. Based on the fuzzy extension of MAVT method, the FMAA is implemented and then applied to a case study, and its results are compared with other well-known MCDA methods in order to show its validity, interpretability and consistency. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：262 / 271

页数：10

共 48 条

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