Asymmetric normalized probabilistic linguistic term set based on prospect theory and its application to multi-attribute decision-making

The probabilistic linguistic term set (PLTS) shows great superiority in expressing decision-makers’ opinions. The multi-attribute decision-making (MADM) problem under a PLTS environment has gained attention from numerous scholars. However, the majority of current studies are not precise enough in ca...

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Published in:Soft computing (Berlin, Germany) Vol. 27; no. 15; pp. 10427 - 10445
Main Authors: Zhang, Jiarong, Li, Meijuan, Lu, Jincheng
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2023
Springer Nature B.V
Subjects:
Air quality
Artificial Intelligence
Asymmetry
Attitudes
Attributes
Behavioral decision theory
Computational Intelligence
Control
Decision makers
Decision making
Decision theory
Diminishing marginal utility
Dominance
Engineering
Entropy
Expected values
Function
Fuzzy Systems and Their Mathematics
Information systems
Linguistics
Mathematical Logic and Foundations
Mechatronics
Novels
Probability
Property
Prospect theory
Rationality
Robotics
Theoretical linguistics
PROMETHEE
Prospect theory
Asymmetric normalized PLTS
MADM
ISSN:1432-7643, 1433-7479
Online Access:Get full text
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Summary:The probabilistic linguistic term set (PLTS) shows great superiority in expressing decision-makers’ opinions. The multi-attribute decision-making (MADM) problem under a PLTS environment has gained attention from numerous scholars. However, the majority of current studies are not precise enough in capturing information on PLTS. To address this problem, this paper presents a preference ranking organization method for enrichment of evaluations (PROMETHEE) based on the redefined PLTS and novel score function to solve MADM problems under a PLTS environment. First, an asymmetric normalized PLTS based on prospect theory (ANPLTSPT) is developed. Compared with the PLTS, ANPLTSPT offers a more realistic portrayal of decision-makers’ psychological state while ensuring the superiority of the PLTS. Second, regarding the structural complexity of ANPLTSPT, this paper attempts to simplify the computational process through a score function that can embody the characteristics of ANPLTSPT. Inspired by previously formulated score functions, a novel score function called Score-InInHe is developed, the corresponding definitions are given, and some further properties are discussed. With the support of the proposed Score-InInHe, the total score entropy is defined and an objective method to determine the attribute weights is proposed. Finally, the proposed approach is applied to the selection of a green supplier and the determination of air quality. The validity and realistic applicability of the proposed approach are demonstrated through comparative analyses and discussions.
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ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-023-08495-0