Unmanned Aerial Vehicle Delivery Scheduling Algorithm under the Background of Smart Supply Chain

With the rapid development of e-commerce and logistics industries, traditional delivery methods face problems such as low efficiency, high cost, and slow response speed. This paper aims to study the drone delivery scheduling algorithm in the context of intelligent supply chain to improve delivery efficiency and customer satisfaction. First, a mathematical model of drone delivery is established, considering factors such as delivery time, cost, load limit, and path optimization. Then, the drone delivery path is optimized using a genetic algorithm, and a new scheduling scheme is generated through selection, crossover, and mutation operations. At the same time, the particle swarm optimization algorithm is combined to adjust the take-off and delivery sequence of the drone to further shorten the delivery time. In the experiment, the average delivery time of the proposed algorithm for 22 delivery tasks was 7.5 hours. The drone delivery scheduling algorithm significantly improves the overall delivery efficiency and provides strong support for the implementation of the intelligent supply chain.