A two-sided matching decision-making approach based on prospect theory under the probabilistic linguistic environment

This paper aims to propose a two-sided matching decision-making approach with the probabilistic linguistic evaluations. Existing two-sided matching decision-making methods rarely consider the psychological behaviors of the subjects, which makes the matching result deviate from the reality. To overco...

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Vydané v:	Soft computing (Berlin, Germany) Ročník 26; číslo 8; s. 3921 - 3938
Hlavní autori:	Jia, Xiang, Wang, Xin-Fan, Wang, Ying-Ming, Zhou, Lang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2022
Predmet:	Artificial Intelligence Computational Intelligence Control Engineering Mathematical Logic and Foundations Mechatronics Robotics Soft Computing in Decision Making and in Modeling in Economics Probabilistic linguistic term sets Prospect theory Two-sided matching Optimal model
ISSN:	1432-7643, 1433-7479
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