城市物流无人机运输路径规划

Urban Logistics UAV Transportation Path Planning

针对城市环境下物流无人机运输路径规划问题,结合无人机运行特点和物流配送场景,充分考虑顾客取、寄件需求和配送时间窗要求,建立物流无人机路径规划模型.对模型进行分层处理,利用模拟退火算法求解无人机配送顺序,采用改进A^(*)算法求解各配送点间的飞行路径.结果表明:以运输成本最小为目标具有实际意义,比传统最短路径方案节省3.4%的能耗;通过调节各子目标函数权重系数,可得到不同运输路径,且规划结果取决于物流公司对运输成本的控制及对客户满意度的重视程度;分析算法时长可知,相比传统A^(*)算法,改进A^(*)算法运行时长缩短4.3%,求解效率提高.

Aiming at the transportation path planning problem of logistics UAV in urban environment, combined with the operation characteristics of UAV and the logistics distribution scene, the path planning model of logistics UAV was established with full consideration of customer’s demand for pickup and delivery and the requirements of distribution time window. The model was layered and the distribution order of UAV was solved by simulated annealing algorithm. Then, the flight path between distribution points was solved by improved A^(*) algorithm. The results show that it is of practical significance to minimize the transportation cost, which saves 3.4% energy consumption compared with the traditional shortest path scheme. By adjusting the weight coefficient of each sub-objective function, different transportation routes can be obtained, and the planning result depends on the logistics company’s control of transportation costs and the importance it attaches to customer satisfaction. The analysis of algorithm duration shows that compared with the traditional A^(*) algorithm, the running time of the improved A^(*) algorithm is shortened by 4.3%, and the solving efficiency is improved.