Abstract
In this article, we study the design problem of a reliable stochastic supply chain network in the presence of random disruptions in the location of distribution centers (DCs) and the transportation modes. It is assumed that a disrupted DC does not necessarily fail the whole of its capacity, and may lose a fraction of that, and rest of demand can be served by other DCs. We introduce a new strategy called soft-hardening strategy where the fraction of the lost capacity depends on the amount of investment for opening and operating. Additionally, the conditional value-at-risk (CVaR) approach is applied to control the risk of model. Finally, to solve the model, first we present an exact solution method by reformulating the problem as a second-order cone programming model, and second a hybrid algorithm combining tabu search and simulated annealing algorithms is developed.
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