Joint inventory-location problem under the risk of probabilistic facility disruptions

This paper studies a reliable joint inventory-location problem that optimizes facility locations, customer allocations, and inventory management decisions when facilities are subject to disruption risks (e.g., due to natural or man-made hazards). When a facility fails, its customers may be reassigned to other operational facilities in order to avoid the high penalty costs associated with losing service. We propose an integer programming model that minimizes the sum of facility construction costs, expected inventory holding costs and expected customer costs under normal and failure scenarios. We develop a Lagrangian relaxation solution framework for this problem, including a polynomial-time exact algorithm for the relaxed nonlinear subproblems. Numerical experiment results show that this proposed model is capable of providing a near-optimum solution within a short computation time. Managerial insights on the optimal facility deployment, inventory control strategies, and the corresponding cost constitutions are drawn.

► A reliable inventory-location model is proposed for optimal facility location and inventory management under facility disruptions.
► The model allows customer re-assignments and minimizes the expected total system cost across all facility disruption scenarios.
► A customized Lagrangian relaxation approach is developed for the mixed-integer nonlinear formulation.
► Numerical experiments are conducted to demonstrate the model performance and draw managerial insights.