A Stochastic Programming Model for Emergency Supplies Distribution Considering Facility Disruption

The main challenge of emergency supplies distribution is addressing facility disruption caused by secondary disasters (e.g., aftershocks and landslides) and handling the uncertainty of road conditions, which can result in an increase in transportation cost and a delayed arrival time. Considering the risk of facility disruption and multiple types of vehicles, a stochastic programming model is established with the goal of minimizing the transportation cost and rental cost. Since distribution center disruption occurs frequently in practical problems, the model considers distribution center disruption instead of supplier disruption. In the first stage, the supplier transports the supplies needed to the distribution center; in the second stage, the distribution center conducts delivery according to the requirements of the affected locations. A modified evolutionary algorithm is designed to solve the proposed model for large-scale emergencies. Based on the real-world case of the Ya'an earthquake in China, numerical experiments are presented to study the applicability of the proposed model and demonstrate the effectiveness of the proposed algorithm. The numerical analysis results indicate that the proposed model can improve the robustness of the emergency supplies distribution network effectively.