基于语言偏好信息的满意公平稳定双边匹配方法

针对语言偏好信息下的双边匹配问题,提出一种考虑匹配满意性、公平性和稳定性的双边匹配方法.首先,通过构造匹配满意度计算规则,将双边主体的语言偏好信息转化为匹配满意度;然后,给出满意匹配、公平匹配和稳定匹配的定义,在此基础上,考虑稳定匹配约束条件,建立双边匹配多目标优化模型,采用理想点法将多目标优化模型转化为单目标规划模型进行求解;最后,通过一个算例验证了提出方法的可行性和有效性.

Satisfied,fair and stable two-sided matching method based on linguistic preference information

A two-sided matching method considering satisfaction, fairness and stability of the matching is proposed to solve two-sided matching problems with linguistic preference information. Firstly, linguistic preference information of agents on both sides are transformed into matching satisfaction degree by developing the calculating rules of matching satisfaction degree. Secondly, concepts on satisfaction, fairness and stability of the matching are given. Furthermore, considering the stable matching constraint condition, a multiple objective optimization two-sided matching model is constructed. Then, the ideal point method is used to convert the multiple objective optimization model into a single objective programming model, which produces the two-sided matching results. Finally, an example is given to prove the feasibility and validity of the proposed method.