Dynamic Matching Decision Method for Emergency Capacity Allocation in Disaster Scenarios

In response to the issue of low efficiency in emergency material dispatching post-disaster, this paper addresses the challenge of emergency transportation capacity allocation with multiple initial points. The objective is to minimize the emergency capacity transportation time, maximize the satisfaction level of emergency transportation capacity matching, and minimize the cost of emergency transportation capacity, while considering constraints, including capacity load limits, type restrictions, quantity limits, and minimum satisfaction level requirements. A dynamic matching decision optimization model for emergency transportation capacity allocation has been developed and solved using a genetic algorithm incorporating an elite strategy. The results indicate that this model is effective for dynamic emergency transportation capacity scheduling in disaster scenarios, adequately addressing the dynamic matching issue of emergency transportation capacity in complex scenarios involving multiple nodes and various types of transportation capacity. It offers decision support for the matching and scheduling of emergency materials and capacity in disaster scenarios.