Hybrid approach for huge multi-stage logistics network optimization under disruption risk

Abstract

Modern supply chains are expanding globally and are subject to a wide range of risks, such as demand uncertainty, natural disasters, and terrorist attacks. This study investigates a huge multi-stage logistics network design problem with facility disruption that could be caused by various risks. Discussing prospects for risk management against facility disruption, we have formulated a probabilistic programming problem. To find a solution for this design issue, we have proposed an effective hybrid method composed of the metaheuristic method and graph algorithms to offset potential losses from the network disruptions. Finally, the effectiveness of the proposed method is validated through numerical experiments.

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