A robust and multi-period model for an emergency logistics network considering the risk of disruptions

Given facility disruptions and uncertainties after disasters, we propose a hybrid multi-period scenario-based robust model (HMSR) to optimize emergency response. This model aims to select appropriate facility locations, organize casualty evacuation, and coordinate relief supply distribution, while minimizing both deprivation cost and operational cost. We utilize the scenario-based robust method to reduce the impact caused by the risks of facility disruptions, and the interval robust method to handle the uncertainty of casualty numbers. In addition, we examine the performance of this model through case studies based on the 2008 Wenchuan earthquake. The proposed model demonstrates its advantages by comparing it with a single-period model, a model that addresses multiple disruption scenarios using stochastic programming, and a model that does not account for the uncertainty in casualty numbers. The sensitivity analysis results indicate that the proposed model can improve rescue efficiency during disasters and reduce deprivation costs to some extent.