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以B2C型电子中介中买卖双方商品交易为实际背景,研究了模糊信息且需求不可分情形下多属性商品交易的优化匹配问题.首先,在给出问题描述的基础上,建立了电子中介中具有模糊信息且需求不可分的多属性商品交易匹配模型,并从买卖双方视角提出了新的基于改进模糊信息公理的交易匹配度计算方法.模型属于一类带约束的非线性多目标通用指派问题,其优化目标是实现买卖双方交易匹配度和交易数量的最大化.接着,针对模型的特点和NP-hard性质,设计了一种新颖的多目标离散差分进化算法对之进行求解.最后,通过多个数值算例的计算并与相关算法进行对比分析,说明了模型的可行性和算法的有效性,
Based on the actual background of B2C transaction between buyer and seller, this paper studies the problem of optimal matching of multi-attribute transaction under the circumstance of fuzzy information and demand.Firstly, based on the description of the problem, Information and demand inseparable multi-attribute commodity transaction matching model, and puts forward a new transaction matching degree calculation method based on improved fuzzy information axiom from the perspective of both buyer and seller.The model belongs to a class of constrained nonlinear multi-objective general assignment problem, and its optimization The goal is to maximize the transaction matching degree and the number of transactions between the buyer and the seller.According to the characteristics of the model and NP-hard properties, a novel multi-objective discrete difference evolutionary algorithm is designed to solve the problem.Finally, The calculation of the examples and comparison with the relevant algorithms illustrate the feasibility of the model and the effectiveness of the algorithm,