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Intuitionistic fuzzy MABAC method based on cumulative prospect theory for multiple attribute group decision making
Author(s) -
Zhao Mengwei,
Wei Guiwu,
Chen Xudong,
Wei Yu
Publication year - 2021
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22552
Subject(s) - operability , group decision making , computer science , vikor method , stability (learning theory) , group (periodic table) , fuzzy logic , operations research , cumulative prospect theory , construct (python library) , mathematical optimization , data mining , artificial intelligence , mathematics , machine learning , mathematical economics , chemistry , organic chemistry , expected utility hypothesis , software engineering , political science , law , programming language
Abstract Intuitionistic fuzzy sets are often employed to depict complex and uncertain environments. The purpose of this article is to construct a new approach for dealing with multiattribute group decision making (MAGDM) problems. In this paper, we introduce the concept of cumulative prospect theory (CPT) into the original multiattributive border approximation area comparison (MABAC) method and create the intuitionistic fuzzy MABAC method based on CPT (CPT‐IF‐MABAC method). The new CPT‐IF‐MABAC method not only has fairly strong operability, but also inherits the characteristic of CPT that considers the influence of decision makers' attitude. Furthermore, this new model mixes together the determination method of attribute weight and alternative. At the end, the stability and availability of this method are demonstrated through an application instance about cold chain and the comparison with the existing methods, such as IF‐MULTIMOORA method and IF‐VIKOR method. In the future, we devote ourselves to explore more applications of this new proposed method and other more effective solutions for MAGDM.