摘要
在考虑物流配送中心建设规模的基础上,结合B2C电子商务企业顾客需求的特点, 利用分级聚类法模糊估计各个顾客的单位商品配送运输费用,建立了B2C电子商务中物流配送中心优化设计的数学模型.该模型属于混合0-1的模糊非线性规划模型,且具有NP难性质.为求解上述模型,首先将其进行清晰化转换,然后采用嵌入表上作业法的遗传算法求解.通过算例验证了模型和算法的有效性和可行性,为B2C电子商务企业物流配送中心的合理设计提供了新的思路.
Based on the size of logistic distribution centers and the characteristics of what the customers demand for business-to customer （B2C） e-commerce companies, a mathematical model is developed to optimize the design of the distribution centers with a hierarchical agglomerative clustering method used to estimated the fuzzy cost of distribution transport from distribution centers to customers. The model is in fact a mixed 0 - I non-linear fuzzy programming model with NP-hard complexity. It is converted into a clearer one which is solved by a genetic algorithm developed in terms of embedded tabular operation. The effectiveness and feasibility of the model and algorithm are verified by an actual computational example, thus providing a new way for the rational design of distribution centers for B2C e-commerce companies.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2005年第8期729-732,共4页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(70431003).
关键词
电子商务
B2C
物流
配送中心
分级聚类
模糊规划
遗传算法
e-commerce
B2C
logistics
distribution center
hierarchical agglomerative clustering
fuzzy programming
genetic algorithm
