Emergency Material Scheduling Optimization Method Using Multi-Disaster Point Distribution Approach

Abstract

The outbreak of multiple disaster sites during the coronavirus disease 2019 (COVID-19) pandemic has presented challenges due to varying access time intensity, population density, and medical resources at each site. To address these issues, this study focuses on 13 districts and counties in Wuhan, China. The importance of each research area is analyzed using the improved PageRank and TOPSIS algorithms to determine the optimal site selection plan. Additionally, a particle swarm algorithm is used to construct an emergency material dispatching model that targets both distribution and site selection costs to solve the multi-distribution center dispatching problem. The results suggest that constructing 10 distribution centers can satisfy the demand for epidemic prevention and control in Wuhan city while saving costs associated with site selection and material distribution. Compared to the previous optimal solution, the distribution and site selection costs under the optimal solution decreased by 27.9% and 17.82%, respectively. This approach can serve as a basis for dispatching emergency materials during public health emergencies.