Abstract
Although disruption risks may occur with a low probability in a supply chain network, they have negative financial impacts and also the recovery process from their destructive effects is very slow. This paper proposes a reliability model for an integrated forward-reverse logistics network design, which can cope with both partial and complete facility disruptions. The reliability model is formulated as a stochastic robust programming whose objective function is to minimise the fixed opening costs of facilities and the expected cost of disruption scenarios, including processing costs, transportation costs, and penalty costs for non-satisfied demands. For doing so, a recent robust optimisation approach is modified to protect the concerned network against partial and complete capacity disruptions. Furthermore, a stochastic programming is employed to account for all interested scenarios. Three numerical experiments are designed to study the effect of capacity disruptions on the concerned logistic network. Finally, the results of the proposed model are compared with the conventional robust optimisation models.
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