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Published in: Soft Computing 17/2019

07-08-2018 | Methodologies and Application

An enhanced approach for two-sided matching with 2-tuple linguistic multi-attribute preference

Authors: Yang Lin, Ying-Ming Wang, Kwai-Sang Chin

Published in: Soft Computing | Issue 17/2019

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Abstract

This paper focuses on multi-attribute two-sided matching with 2-tuple preferences. A new framework consisting of paring process and feedback process is proposed to generate matching results (couples) in multiple stages. According to the assumption that matching couples should be satisfied with each other, the concept of expected matching ordinal (EMO) is defined and used for filtering unqualified couples in each stage. To derive optimal results, payoff matrices and preference ordinals are firstly obtained on the basis of the preferences given by two-sided players. The paring process formulates a bi-objective optimization model to generate primary matching couples based on the payoff matrices. Subsequently, the feedback process identifies targeted couples from them with the EMO constraint. This mechanism is performed to ensure that matching couples are all mutually satisfied. The novelty of our approach is that we manage matching decisions by balancing individual benefit and party’s benefit. Finally, a practical example is given to illustrate the proposed approach and comparison analysis shows the advantages of our approach. Some related issues are further discussed.

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Metadata
Title
An enhanced approach for two-sided matching with 2-tuple linguistic multi-attribute preference
Authors
Yang Lin
Ying-Ming Wang
Kwai-Sang Chin
Publication date
07-08-2018
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 17/2019
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3436-y

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