An integrated supply chain design model with random disruptions consideration

This paper investigates a supply chain design problem where distribution centers are subject to random disruptions. As a result of disruptions, one or more of the distribution centers may fail to serve the customers. It is assumed that customers have random demands; thus, each distribution center maintains some amount of safety stocks in order to provide suitable service level for the customers it serves. The proposed model for this study is formulated as a nonlinear integer programming to minimize the expected total cost which includes costs of location, inventory, transportation and lost sales. The model simultaneously determines the location of distribution centers and the allocation of customers to distribution centers. In order to solve the resulted mathematical model, an efficient solution approach based on genetic algorithm is developed. Finally, computational results for several instances of the problem are presented to demonstrate the effectiveness of the proposed algorithm.

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