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A Two-Echelon Cooperated Routing Problem for a Ground Vehicle and Its Carried Unmanned Aerial Vehicle

机译:地面车辆及其运载式无人飞行器的两级协作路径问题

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摘要

In this paper, a two-echelon cooperated routing problem for the ground vehicle (GV) and its carried unmanned aerial vehicle (UAV) is investigated, where the GV travels on the road network and its UAV travels in areas beyond the road to visit a number of targets unreached by the GV. In contrast to the classical two-echelon routing problem, the UAV has to launch and land on the GV frequently to change or charge its battery while the GV is moving on the road network. A new 0–1 integer programming model is developed to formulate the problem, where the constraints on the spatial and temporal cooperation of GV and UAV routes are included. Two heuristics are proposed to solve the model: the first heuristic (H1) constructs a complete tour for all targets and splits it by GV routes, while the second heuristic (H2) constructs the GV tour and assigns UAV flights to it. Random instances with six different sizes (25–200 targets, 12–80 rendezvous nodes) are used to test the algorithms. Computational results show that H1 performs slightly better than H2, while H2 uses less time and is more stable.
机译:本文研究了地面车辆(GV)及其运载的无人飞行器(UAV)的两级协作路径问题,其中地面车辆(GV)在道路网络上行驶,而无人机在道路以外的地区行驶,以访问地面GV未达到的目标数量。与经典的两级路由问题相反,当GV在道路网络上行驶时,UAV必须频繁发射并降落在GV上才能更换或充电。开发了一个新的0-1规划模型来解决这个问题,其中包括了对GV和UAV航线的时空协作的约束。提出了两种启发式方法来解决该模型:第一种启发式方法(H1)为所有目标构建完整的巡回路线,并按GV路线划分,而第二种启发式方法(H2)构造GV巡回路线并为其分配无人机飞行。使用具有六个不同大小(25-200个目标,12-80个集合点的节点)的随机实例来测试算法。计算结果表明,H1的性能略好于H2,而H2使用的时间更少且更稳定。

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