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AN ENHANCEMENT EDAS METHOD BASED ON PROSPECT THEORY
Author(s) -
Yan Huang,
Rui Lin,
Xudong Chen
Publication year - 2021
Publication title -
technological and economic development of economy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.634
H-Index - 47
eISSN - 2029-4921
pISSN - 2029-4913
DOI - 10.3846/tede.2021.15038
Subject(s) - edas , computer science , mathematical optimization , prospect theory , rationality , selection (genetic algorithm) , decision theory , risk analysis (engineering) , management science , artificial intelligence , mathematics , engineering , estimation of distribution algorithm , economics , business , statistics , finance , political science , law
Decision-making is the process of carefully considering multiple options and choosing the best one. The EDAS (evaluation based on distance from average solution) method has been studied in many multi-attributes decision-making (MADM) problem which assumes decisionmaking under absolute rationality. However, people usually show the characteristics of bounded rationality in the real decision-making process. Prospect theory (PT) utilizes gains and losses relative to the reference point to explain this phenomenon better. In this paper, an enhancement EDAS method based on PT will be proposed, which shows better properties in practice. We apply the traditional EDAS method and enhancement EDAS method to the same case and we utilize the sensitivity analysis and comparative analysis to analyze their performances. The result shows that our approach has a superiority compared with the traditional EDAS method. The methods we present are of great significance for investment decision-making problems, new product development, design plan selection and supplier selection.

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