Abstract
Supply chain network design (SCND) is the process for designing and modeling the supply chain such that to minimize the costs generated by the location of facilities and the flow of product between the selected facilities. The aim of this paper is to investigate a particular SCND, namely the two-stage supply chain network design problem with risk-pooling and lead times and to provide a novel efficient and effective genetic algorithm (GA) designed to fit the challenges of the considered optimization problem. Extensive computational experiments were performed on two sets of instances and the achieved results prove the performance of our proposed GA.
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