UAV Path Planning Based on Variable Neighborhood Search Genetic Algorithm
UAV Path Planning Based on Variable Neighborhood Search Genetic Algorithm
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DOI：
10.1007/978-3-030-78811-7_20
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Guo Zhang;Rui Wang;Hongtao Lei;Tao Zhang;Wenhua Li;Yuanming Song
中科院分区：
文献类型：
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作者：
Guo Zhang;Rui Wang;Hongtao Lei;Tao Zhang;Wenhua Li;Yuanming Song
This study proposed a new genetic algorithm with variable neighbourhood search (GAVNS) for UAV path planning in three-dimensional space. First, an 0–1 integer programming mathematical model is established by inspired from the vehicle routing planning model with time window (VRPTW), and then a heuristic rule based on space vector projection is designed to quickly initialize high-quality solutions that meet constraints of upper error limit and minimum turning radius. Second, it improves mutation operator with a reselected mutation strategy, and incorporates Variable Neighborhood Search strategy based on adding and deleting route during the search process; Finally, GAVNS is compared with general Genetic Algorithm on a set of experiments. It is demonstrated that GAVNS algorithm is both effective and efficient. Moreover, the introduction of variable neighborhood search strategy enhances the local search ability of Genetic Algorithm.
