UAV Group Distribution Route Optimization Under Time‐Varying Weather Network

作者：Wanchen Jie, Cheng Pei, Yan Hong, Weitong Lin · 发表于：International Journal of Intelligent Systems · 年份：2025 · DOI：10.1155/int/8682162 · 被引用次数：1 · 研究领域：UAV Applications and Optimization、Robotic Path Planning Algorithms、Distributed Control Multi-Agent Systems

The rapid advancement in unmanned aerial vehicle (UAV) technology has marked a transformative shift in various industries, with logistics distribution service being one of the prime sectors reaping the benefits. UAVs offer substantial benefits in speed, cost, and reach, promising to revolutionize logistics, especially in remote areas. On the one hand, they are poised to meet demands for quick and versatile delivery options. On the other hand, their deployment comes with challenges. Weather variabilities such as rainfall, wind speed, and the need for safe take‐off intervals can compromise UAV safety and operation. Conventional route optimization often overlooks these dynamic factors, resulting in inefficient or unworkable delivery routes. The repeated time‐consuming calculations are caused by repeated trials when making UAV group distribution plans. Recognizing these gaps, this study proposes a data representation to effectively transform the flight flyable area of UAVs into a time‐varying network that maintains spatiotemporal connectivity and establishes a mathematical model that represents the complexities of UAV group distribution. Then, a multistage dynamic optimization algorithm specifically tailored for large‐scale time‐varying network distribution route search is designed to obtain the stable and optimal solution. Subsequent experimental validations on actual case datasets have confirmed the correctness, effectiveness, and adaptability of the algorithm. Benchmarking aga...