A Hesitant Fuzzy Bilateral Matching Behavior Decision-Making Method Based on the Satisfaction and Fairness Considering Risk Attitudes
In view of the fact that most subjects in bilateral matching decision-making tend to be more and more bounded rationality,a matching method based on TODIM combining the bilateral satisfaction and fairness is proposed considering the risk attitude of matching subjects.First,the bilateral matching problem with hesitant fuzzy preference information is described.Second,the average of the overall dominance of each subject is calculated according to TODIM method and then is normalized;Based on this,the different risk attitudes of both parties are considered to obtain the satisfaction and fairness of bilateral subjects.Then,multiple matching optimization models including unilateral subject satisfaction,bilateral subject satis-faction and fairness are established.The best matching scheme can be obtained by solving these models and compared with other methods.Finally,a numerical example is given to verify the feasibility of the presented method.The main innovations of this paper are as follows:1)A satisfaction calculation method considering the TODIM idea and risk attitude is proposed;2)A fair degree calculation method considering the TODIM idea and risk attitude is proposed;3)Several different matching models are established by combining the satisfaction of unilateral subjects,satisfaction of bilateral subjects and fairness.
Bilateral matching behavior decision-makinghesitant fuzzy numbersatisfactionfairnessmatching model
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