A study on optimizing the location selection problem for urban UAV distribution while accounting for obstacles

This study addresses the location problem of UAV distribution centers for urban logistics services by establishing a mathematical model aimed at minimizing the total cost of UAV operations. The model incorporates various constraints, including the number of supply points, maximum distribution capacity, task-specific limitations, starting point restrictions, maximum flight distance for UAVs, altitude constraints, and obstacle avoidance requirements. This paper presents a UAV delivery flight path obstacle avoidance algorithm designed to effectively navigate obstacles in urban environments. Additionally, a genetic annealing fusion algorithm is developed to address the distribution center location model. Comparative analysis reveals that incorporating obstacle avoidance significantly enhances performance compared to scenarios without it, and the genetic annealing algorithm outperforms the traditional genetic algorithm. Finally, a sensitivity analysis is conducted on the number of distribution centers and obstacles.