Location–allocation problem in the emergency logistics system considering lateral transshipment strategy

This paper explores the problem of designing an efficient emergency logistics system while considering lateral transshipment strategy. Firstly, a two-stage mixed-integer programming model is proposed to characterize the location–allocation problem in an emergency logistics system with the aim of minimizing the total cost. Secondly, we propose an improved Benders decomposition framework for solving the emergency logistics system model. The numerical results reveal that our algorithm can find the optimal solution efficiently for large-scale instances, outperforming the commercial programming solver Gurobi. Finally, using Poyang Lake in China as a case study, we demonstrate that the lateral transshipment strategy can reduce the total cost of the emergency logistics system by 8.3% through comparing with the one without considering the lateral transshipment strategy. At the same time, we argue that the equity factor prevents the affected people from being evacuated to more distant shelters. The contribution of our work can be summarized as follows: an improved Benders decomposition algorithm is developed to investigate the optimal design of location–allocation strategy in the three-level emergency logistics network, with the consideration of lateral transshipment strategy and equity factor.