TY - JOUR
T1 - Stable two-sided matching decision making with incomplete fuzzy preference relations
T2 - A disappointment theory based approach
AU - Zhang, Zhen
AU - Kou, Xinyue
AU - Palomares, Iván
AU - Yu, Wenyu
AU - Gao, Junliang
N1 - Funding Information:
This work was partly supported by the National Natural Science Foundation of China (NSFC) under Grant 71501023 , Grant 71971039 and Grant 71771034 , the Funds for Creative Research Groups of China under Grant 71421001 , the Key Program of the NSFC, China under Grant 71731003 , the Scientific and Technological Innovation Foundation of Dalian, China under Grant 2018J11CY009 and Grant 2018JQ69 , and the Research Funds for Young Scholars from the Education Department of Liaoning Province, China under Grant LN2017QN027 .
Funding Information:
This work was partly supported by the National Natural Science Foundation of China (NSFC) under Grant 71501023, Grant 71971039 and Grant 71771034, the Funds for Creative Research Groups of China under Grant 71421001, the Key Program of the NSFC, China under Grant 71731003, the Scientific and Technological Innovation Foundation of Dalian, China under Grant 2018J11CY009 and Grant 2018JQ69, and the Research Funds for Young Scholars from the Education Department of Liaoning Province, China under Grant LN2017QN027.
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/11
Y1 - 2019/11
N2 - Practical two-sided matching decision making problems, such as marriage matching and person-job matching, are often characterized by a lack of knowledge and time constraints. Therefore, matching objects tend to provide comparative preferential information over other matching objects represented by incomplete fuzzy preference relations. In this paper, it is proposed a new approach to stable two-sided matching decision making with incomplete fuzzy preference relations based on disappointment theory. In the proposed approach, the subjective satisfaction degrees of each matching object on one side over matching objects on the other side are first calculated based on priority weight vectors derived from incomplete fuzzy preference relations. Based on disappointment theory, both the disappointment and elation degrees associated with each matching object over matching objects on the other side are calculated. This process is undertaken by considering the probability of each possible matching pair, which are further used to derive the adjusted satisfaction degrees of matching objects. Afterwards, a stable matching optimization model that aims to maximize the total adjusted satisfaction degrees of both sides is constructed by considering stable matching conditions under incomplete information. The optimal stable matching result can be further determined by solving the optimization model. Finally, a numerical example and some comparative studies are presented to demonstrate the characteristics, innovations and added value of the proposed approach.
AB - Practical two-sided matching decision making problems, such as marriage matching and person-job matching, are often characterized by a lack of knowledge and time constraints. Therefore, matching objects tend to provide comparative preferential information over other matching objects represented by incomplete fuzzy preference relations. In this paper, it is proposed a new approach to stable two-sided matching decision making with incomplete fuzzy preference relations based on disappointment theory. In the proposed approach, the subjective satisfaction degrees of each matching object on one side over matching objects on the other side are first calculated based on priority weight vectors derived from incomplete fuzzy preference relations. Based on disappointment theory, both the disappointment and elation degrees associated with each matching object over matching objects on the other side are calculated. This process is undertaken by considering the probability of each possible matching pair, which are further used to derive the adjusted satisfaction degrees of matching objects. Afterwards, a stable matching optimization model that aims to maximize the total adjusted satisfaction degrees of both sides is constructed by considering stable matching conditions under incomplete information. The optimal stable matching result can be further determined by solving the optimization model. Finally, a numerical example and some comparative studies are presented to demonstrate the characteristics, innovations and added value of the proposed approach.
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U2 - 10.1016/j.asoc.2019.105730
DO - 10.1016/j.asoc.2019.105730
M3 - Article
AN - SCOPUS:85071293471
SN - 1568-4946
VL - 84
JO - Applied Soft Computing Journal
JF - Applied Soft Computing Journal
M1 - 105730
ER -