Two-sided matching decision making based on heterogeneous incomplete preference relations

Two-sided matching problems exist widely in human beings' daily life. In this paper, two-sided matching decision making problems with heterogeneous incomplete preference relations are investigated. In order to obtain the optimal matching between matching objects on both sides, the priority weight vectors are firstly derived from each matching object's incomplete fuzzy or multiplicative preference relation over matching objects on the other side. Based on the priority weight vector, each matching object's satisfaction degrees over matching objects on the other side are calculated, based on which a bi-objective linear binary programming model is constructed and solved to determine the optimal matching. Finally, an example for employee-position matching is provided to illustrate the proposed approach.