灰色双边公平匹配决策模型

Grey fair matching decision–making model

摘要:

针对含有灰色、模糊等不确定信息的双边匹配决策问题,从匹配主体的满意度、匹配方案的公平性角度,构建一种新的灰色双边公平匹配决策模型。文中,首先给出了灰色匹配信息系统和公平匹配的概念,利用灰靶决策方法测度匹配主体的满意度,建立基于匹配距离最小、匹配距离偏差最小的多目标优化模型,并运用线性加权法将多目标匹配模型进行转化为单目标优化模型求解匹配方案；最后,利用其解决产学研合作匹配对象选择问题。结果表明,本文所提出的模型综合考虑了匹配主体的满意度和匹配方案的公平性,能够很好地描述和解决不确定信息的双边匹配决策问题,为管理者和决策者处理产学研合作选择决策问题提供方法支撑。

Abstract:

In order to do with the bilateral matching decision–making problems with grey and fuzzy information, from the angle of the satisfaction degree of matching stakeholders, and fairness of matching schemes, a novel grey bilateral fair matching decision–making model is established. In this paper, to begin with, some concepts of grey matching information system and fair matching are defined, and then grey target decision-making is utilized to measure the satisfaction degree of matching stakeholders; what’s more, a multi-objective optimal model based on the minimum of matching distance and their deviation is established, and then it is transformed to a single objective optimization model by taking advantage of the linear weighting method, so that the matching schemes are solved; finally, this novel model is applied to the selection decision-making of the matching objects on industry-university-research (I-U-R)collaboration. The results that the proposed model fully considers the satisfaction degree of matching stakeholders, and the stabilities and fairness of matching schemes, and could well describe and resolve the uncertain information, which can provide for managers and decision makers a support of method do with bilateral matching problems on I-U-R collaboration.