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机构地区:[1]淮海工学院机械工程学院
出 处:《数学的实践与认识》2018年第5期63-71,共9页Mathematics in Practice and Theory
基 金:江苏省科技计划项目(BY2016056-05)
摘 要:针对决策信息获取困难的情况采用不同粒度的模糊语言表达属性值,并提出了一种不同粒度模糊语言一致化方法.针对线性加权存在的决策补偿效应,采用基于级别优先序理论的ELECTRE集结基于前景理论的价值函数得到满意度值.传统合作伙伴决策方式只是制造企业对供应商评价并从中选择出评价结果最好的供应商,全然不考虑供应商对制造企业的接受程度,在集中式决策方法中采用双边匹配决策方法构造多目标优化模型,并采用模糊规划中的两阶段法求解多目标优化得到最终匹配结果.实例分析表明该方法的有效性.In view of the case it is difficult to gain access to the detailed decision making information, the ratings were expressed with fuzzy linguistics varying in granularities and a way to uniform the multi-granularity was proposed. In view of the decision-making compensation effects in the linear weighted method, value functions in prospect theory were aggregated with ELECTRE based on the outranking relation theory. In the traditional part- ner selection where only manufactures evaluated suppliers and selected the one which gained the best evaluation result and the result with which suppliers evaluated manufactures was not at all taken into consideration, as such, optimization models for decision making in a cen- tralized scenario were constructed based on two-sided matching considering the both results, and a two-phase fuzzy programming was used to solve the optimization models and obtain the matching results. Finally, an example analysis illustrated the validity of the proposed method.
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