An integrated model for location-inventory problem with random disruptions

This paper studies supply chain design problem in which distribution centers (DCs) are vulnerable to random disruptions. Due to this vulnerability, at any time one or more of DCs may fail to serve the customers. It is assumed that customers have uncertain demands; as a result, each DC retains some amount of safety stocks to provide suitable service level for the customers it serves. We formulate the problem as a nonlinear integer programming model that minimizes the expected total costs including costs of location, inventory, transportation, and lost sales considering random disruptions. The model simultaneously determines the location of DCs and the assignment of customers to DCs. In order to solve this nonlinear integer programming model, an efficient solution method based on genetic algorithm is proposed. At the end, computational results for several instances of the problem are presented to demonstrate the effectiveness of the proposed algorithm.