This paper presents a strategic multi segment, multi period and multi-product supply chain management to meet reliable networks for handling disruptions strike. We present a mixed-integer programming model whose objective is to minimize the expected cost composed of probability and cost of occurrence in each scenario. The proposed model of this paper considers time value of money for each operation and transportation cost. We attempt to minimize expected costs by considering the levels of inventory, back-ordering, the available machine capacity and labor levels for each source, transportation capacity at each transshipment node and available warehouse space at each destination. The problem is generalized by taking into account backup supplier with reserved capacity and backup transshipment node that, which satisfies demands at higher price without disruption facility. We use a priority-based genetic algorithms encoding to solve the proposed problem under multi period and multi product conditions. The performance of the proposed model is examined using some instances.

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