Fuzzy programming model and algorithm for optimal design of distribution centers for B2C e-commerce
With respect to the customer characteristics of little demand, multi-commodity, and dispersed location, a fuzzy programming model is proposed to optimize the design of distribution centers for business-to-consumer (B2C) e-commerce, in which a hierarchical agglomerative clustering method is introduced to classify customers and estimate the unit weight fuzzy delivery cost from distribution centers to customers. Both commodity supplies and customer demands in the whole plan period are treated as fuzzy numbers. The model is nonlinear because of the scale-economy effect. Therefore, it is not easy to obtain the optimal solution with conventional methods. The problem is solved firstly, by converting it into a crisp model, followed by the implementation of a genetic algorithm with particle swarm optimization. The computational results on simulative examples have demonstrated the effectiveness and feasibility of the model and algorithm.
E-commerce distribution centers fuzzy programming particle swarm optimization genetic algorithm
Zhongzhong Jiang Dingwei Wang W.H. Ip
School of Business Administration Northeastern University Shenyang, P.R.China School of Information Science and Engineering Northeastern University Shenyang, P.R.China Department of Industrial and Systems Engineering Hong Kong Polytechnic University Hong Kong, P.R.Chi
国际会议
2007 IEEE International Conference on Automation and Lofistics
山东济南
英文
2007-08-18（万方平台首次上网日期，不代表论文的发表时间）