基于区分矩阵改进的TOPSIS法在第三方物流服务商选择中的应用  

Application of improved TOPSIS method based on differentiation matrix in selection of the third-party logistics service providers

作　　者：李天淳 叶军[1,2] 吕康 LI Tianchun;YE Jun;LV Kang(School of Information Engineering,Nanchang Institute of Technology,Nanchang 330099,China;Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing,Nanchang Institute of Technology,Nanchang 330099,China)

机构地区：[1]南昌工程学院信息工程学院,江西南昌330099 [2]南昌工程学院江西省水信息协同感知与智能处理重点实验室,江西南昌330099

出　　处：《南昌工程学院学报》2021年第6期100-109,共10页Journal of Nanchang Institute of Technology

基　　金：江西省教育厅科学技术研究项目(GJJ170995,GJJ211920);国家自然科学基金资助项目(61663028)。

摘　　要：针对目前将经典粗糙集理论与TOPSIS法相结合的决策模型中,权重确定环节存在一些不足,导致决策结果准确性下降等问题,引入一种区分矩阵的属性重要度定义方法,与粗糙集代数方法进行结合,提出了一种基于组合权重的TOPSIS决策模型。该模型在权重确定环节避免了非核属性权重为零的情况,优化了核属性和非核属性权重所占比例,合理反映了各属性在决策时所起的作用。最后通过第三方物流服务商选择实例分析表明,该方法得到的排序结果更加贴近实际,提高了决策精度。In view of the deficiency in weight determination in the decision model combining classical rough set theory with TOPSIS method,which leads to the decline of the accuracy of decision results,a method of attribute importance definition of discernibility matrix is introduced in the paper.It is combined with rough set algebra method,and a TOPSIS decision model based on combined weight is proposed.The model avoids the case in which the weight of non-core attributes is zero,optimizes the proportion of the weight of core attributes and non-core attributes,and reasonably reflects the role of each attribute in decision-making.Finally,an example of selecting the third-party logistics service providers shows that the ranking results obtained with this method are closer to reality and improve the decision-making accuracy.

关 键 词：粗糙集 逼近理想解排序法 区分矩阵 组合权重 第三方物流 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]