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作 者:乐琦[1]
机构地区:[1]江西财经大学信息管理学院,江西南昌330013
出 处:《运筹与管理》2016年第1期100-104,共5页Operations Research and Management Science
基 金:国家自然科学基金资助项目(71261007;71261006;71361021);教育部人文社会科学基金资助项目(12YJC630289);江西省自然科学基金资助项目(20151BAB201026)
摘 要:针对基于两粒度语言评价信息的双边匹配问题,提出了一种了基于二元语义信息处理的决策方法。在该方法中,首先将两粒度语言评价信息转化为两粒度二元语义信息;考虑以每个主体满意度最大为目标,运用广义二元语义加权平均算子构建了多目标优化模型;进一步地,运用二元语义算术平均算子将多目标优化模型转化为双目标优化模型;根据二元语义的自身特点将双目标优化模型转化为单目标优化模型,进而进行求解来得到匹配方案。最后,给出一个算例说明所提供方法的有效性。With respect to the two-sided matching problem with two-granularity linguistic evaluation information, a decision method based on two-tuple information representation is proposed. In the method, firstly, the two- granularity linguistic evaluation information is transformed into the two-granularity two-tuple information. To max- imize the satisfaction degree of each agent, a multi-objective optimization model by using the extended weighted average operator for linguistic two-tuple is constructed. Further, the multi-objective optimization model is trans- formed into a bi-objective optimization model by using the arithmetic mean operator for linguistic two-tuple. According to the characteristic of two-tuple, the bi-objective optimization model is converted into a single-objec- tive model. The matching alternative can be obtained by solving the model. Finally, an example is given to illus- trate the validity of the proposed method.
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