A two-stage stochastic mixed-integer program for the capacitated logistics fortification planning under accidental disruptions

Highlight
• We model capacitated logistics fortification planning in a two-stage stochastic mixed-integer programming.
• Proposed the risk mitigation combination of facility fortification and emergency inventory pre-positioning policies to against accidental disruptions.
• Developed a disjunctive decomposition-based branch- and-cut (D2-BAC) algorithm.
• Provide a powerful tool for identifying best possible fortification strategies to increase the reliability.

Vulnerability to service disruptions caused by accidents is one of the major threats in existing logistics systems. This paper presents a fortification planning model for capacitated logistics systems in a two-stage stochastic mixed-integer programming framework. Considering limited protection investment budget, the model can deal with locating fortified facilities, pre-positioning emergency inventory and assigning emergency transportation under scenario-based random parameters. The risk mitigation combination of facility protection and emergency inventory pre-positioning policies is proposed to hedge well against accidental disruptions in the capacitated logistics systems. The revised disjunctive decomposition-based branch-and-cut (D2-BAC) algorithm for the model is developed by integrating with two types of valid cuts and dynamical ‘truncation’ strategy of the branch-and-bound tree. Extensive computational results confirm the computational performance of the proposed method and indicate that this model can provide a powerful tool for identifying best possible fortification strategies. It is also demonstrated that the risk mitigation combination can significantly increase the reliability of capacitated logistics systems.