基于混合遗传算法的无人机与车辆协同应急物资配送路径优化研究  

Optimization of Emergency Material Delivery Path for UAV Vehicle Collaboration Based on Hybrid Genetic Algorithm

作　　者：杨新湦[1] 张宇菲 张召悦[3] YANG Xinsheng;ZHANG Yufei;ZHANG Zhaoyue;无(School Office,Civil Aviation University,Tianjin 300300,China;Transportation Science and Engineering College,Civil Aviation University,Tianjin 300300,China)

机构地区：[1]中国民航大学校办公室,天津300300 [2]中国民航大学交通科学与工程学院,天津300300 [3]中国民航大学空中交通管理学院,天津300300

出　　处：《综合运输》2024年第7期130-138,共9页China Transportation Review

摘　　要：为应对突发事件下的应急物资运输问题,将无人机与车辆协同应用在应急场景的路径优化问题中。考虑到应急场景的特殊性与弱经济性,将受灾点进行分类,并以无人机与车辆到达受灾点累计服务时间最小化为目标建立路径优化模型,同时加入无人机自身续航和载重约束、无人机与车辆的协同性约束等,更符合实际应用情况;通过结合遗传算法和自适应大规模邻域搜索算法,设计混合遗传算法进行模型的求解,通过算例验证模型和算法的有效性。算例结果表明:混合遗传算法能够提升求解精度以及求解速度,可为应对突发事件下的应急物资运输提供有效支撑。To address the issue of emergency material transportation in emergency situations,unmanned aerial vehicles and vehicles are synergistically applied in the path optimization problem of emergency scenarios.Considering the particularity and weak economy of emergency scenarios,the disaster hit points are classified according to the reachability of trucks,and a path optimization model is established with the objective of minimizing the cumulative service time of UAVs and vehicles reaching the disaster hit points.At the same time,constraints such as UAV's own endurance and load constraints and the synergy between UAVs and trucks are added,which is more consistent with the actual application situation;A hybrid genetic algorithm was designed to solve the model by combining genetic algorithm with adaptive large-scale neighborhood search algorithm.Finally,the effectiveness of the model and algorithm was verified through numerical examples.The results of the example show that the hybrid genetic algorithm can improve the accuracy and speed of the solution,and can provide effective support for emergency material transportation in response to emergencies.

关 键 词：路径优化 无人机与车辆协同 混合遗传算法 应急物资配送 

分 类 号：U15[交通运输工程]