考虑天气因素的车辆联合无人机配送路径规划  

Vehicle Joint UAV Distribution Path Planning Under Weather Factors

作　　者：赵桂红[1] 秦伟祥 ZHAO Guihong;QINWeixiang(College of Economics and Management,Civil Aviation University of China,Tianjin 300300,China;College of transportation science and Engineering,Civil Aviation University of China,Tianjin 300300,China)

机构地区：[1]中国民航大学经济与管理学院,天津300300 [2]中国民航大学交通科学与工程学院,天津300300

出　　处：《综合运输》2023年第9期148-155,共8页China Transportation Review

基　　金：基于最大似然原理的分层聚类算法研究(61103005)。

摘　　要：传统的车辆联合无人机路径规划问题大都忽略了天气因素对车辆联合无人机配送的影响。本文以配送总成本最小为目标,建立了考虑天气因素下车辆无人机路径问题模型,采用遗传算法求解,并结合算例进行研究。结果表明在考虑天气条件下所求得的最优解,要比没有考虑天气所求得的路径在实际情况下所产生的总成本更低,表明该模型能够更加合理的规划配送路径;同时分析了在不同风向和不同风力大小下,其成本缩少的比率变化。The traditional path planning problem of vehicle joint UAV mostly ignores the influence of weather factors on vehicle joint UAV distribution.Aiming at minimizing the total cost of distribution,a vehicle UAV routing problem model considering weather factors is established,which is solved by genetic algorithm and studied with an example.The results show that the optimal solution under weather conditions is lower than the total cost of the route without weather.It shows that the model can plan the distribution path more reasonably.At the same time,the change of cost reduction rate under different wind directions and different wind sizes is analyzed.

关 键 词：车辆 无人机 路径规划 天气因素 遗传算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]