Research on UAV nest assignment optimization based on particle swarm optimization algorithm

This study addresses the scheduling and assignment issues of UAV nests in the context of electrical power line inspections, characterized by large optimization scales, complex constraints, and multiple objectives. It is proposed a nest scheduling optimization model that incorporates various constraints, and construct an adaptation function aimed at maximizing inspection efficiency and minimizing nest idle time. The particle swarm optimization algorithm is applied to optimize the nest allocation. Simulation experiments demonstrate that the proposed method can effectively managing the variations in UAV numbers and resource constraints, and ensuring efficient resource utilization. The proposed optimization strategy proves to be adaptable and effective across various application scenarios.