A Model for the Allocation of Emergency Supplies under Public Health Emergencies Based on the ACO

Efficient and equitable allocation of emergency medical supplies in the backdrop of sudden public health emergencies has become a critical issue. In this paper, we propose an emergency distribution decision-making approach that integrates facility location optimization with route planning to meet real-world needs. First, using a multi-criteria entropy weight method, we quantify the priority of each demand point and then apply a weighted centroid method to determine the optimal location for distribution centers, ensuring focused response in high-priority areas. On this basis, we develop a multi-objective vehicle routing optimization model that incorporates both priority levels and dynamic time window constraints. To enhance solution quality, we design an improved ant colony optimization (ACO) algorithm by combining the classical ACO with a 2-opt local search and an elite ant strategy, and we conduct comparative experiments against the traditional ACO. Simulation results demonstrate that the improved algorithm outperforms the conventional one in total delivery distance, vehicle utilization, and maximum route length, thereby better securing supply for high-priority areas and improving the overall efficiency and equity of dispatching. The findings of this study provide a scientific theoretical foundation and technical reference for emergency resource allocation during public health crises.