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.

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