多型异构数据下准则具有优先级别的双边匹配决策方法

Two-sided Matching Decision Making Approach under Multi-type Heterogeneous Data Considering Different Priority Levels of Criteria

  • 摘要: 针对多型异构数据下准则之间具有优先级别的双边匹配决策问题,提出了一种基于集对分析二元联系数和优先集结算子的双边匹配决策方法。首先,给出了一种将多型异构数据同构化为二元联系数的方法;其次,定义了二元联系数优先加权几何平均(BCNPWG)算子;然后,基于BCNPWG算子,提出了一种准则值为多型异构数据且准则之间具有优先级别的双边匹配决策方法。该方法先将多型异构数据匹配满意度矩阵转化为二元联系数匹配满意度矩阵,然后利用BCNPWG算子集结得到双方主体的综合匹配满意度矩阵;进一步地,以双方主体的综合匹配满意度总和最大为目标,构建二元联系数多目标匹配优化模型,并利用线性加权法及二元联系数的期望值和均方差将其转化为单目标匹配优化模型,进而通过求解该模型得到双边匹配结果。最后,通过一个算例说明了所提出匹配决策方法的可行性和有效性。

     

    Abstract: With respect to the two-sided matching decision making problems under multi-type heterogeneous data considering different priority levels of criteria, we propose a two-sided matching decision making method based on set pair analysis binary connection number and prioritized aggregation operator. Firstly, we propose an isomorphic method to transform multi-type heterogeneous data into binary connection numbers. Secondly, we define a binary connection number prioritized weighted geometric average (BCNPWG) operator. Thirdly, based on the BCNPWG operator, we develop a method to solve the two-sided matching decision making problems, in which the criterion values are multi-type heterogeneous data and the criteria have different priority levels. In this method, the multi-type heterogeneous data matching satisfaction degree matrices are transformed into binary connection number matching satisfaction degree matrices and the binary connection number matching satisfaction degrees are aggregated by using the BCNPWG operator to obtain the comprehensive

     

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