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.
Abstract
With respect to the fuzzy information and indivisible demand in B2C E-brokerage, the trade matching problem for multi-attribute exchanges is investigated. First, on the basis of the problem description, a mathematic model is built to maximize the matching degree and the trade quantity. The model belongs to a class of nonlinear multi-objective general assignment problems. In this model, a new calculation method of matching degree, which based on the improved fuzzy information axiom from both buyers’ and sellers’ points of view, is proposed. Then, according to the NP-hard complexity and characteristics of the model, a novel multi-objective discrete differential evolution is developed to solve it. Finally, computation on numerical examples and comparison with representative algorithms show the model and algorithm are feasible and effective.
关键词
电子中介 /
模糊信息 /
需求不可分 /
多属性交易匹配 /
多目标优化 /
差分进化算法
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Key words
electronic brokerage /
fuzzy information /
indivisible demand /
multi-attribute trade matching /
multi-objective optimization /
differential evolution
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中图分类号：
N945
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脚注
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基金
国家自然科学青年基金(70801012);中国博士后科学特别基金(200902543);国家创新研究群体科学基金(71021061); 国家自然科学重点基金(70931001)
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