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A matheuristic for the vehicle routing problem with drones and its variants

机译:带有无人机及其变体的车辆路径问题的数学方法

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In this work, we are interested in studying the Vehicle Routing Problem with Drones (VRPD). Given a fleet of trucks, where each truck carries a given number of drones, the objective consists in designing feasible routes and drone operations such that all customers are served and minimal makespan is achieved. We formulate the VRPD as a Mixed Integer Linear Program (MILP), which can be solved by any standard MILP solver. Moreover, with the aim of improving the performance of solvers, we introduce several sets of valid inequalities (VIEQ). Due to limited performance of the solvers in addressing large instances, we propose a matheuristic approach that effectively exploits the problem structure of the VRPD. Integral to this approach, we propose the Drone Assignment and Scheduling Problem (DASP) that, given an existing routing of trucks, looks for an optimal assignment and schedule of drones such that the makespan is minimized. In this context, we propose two MILP formulations for the DASP. In order to evaluate the performance of a state-of-the-art solver in tackling the MILP formulation of the VRPD, the benefit of the proposed VIEQs, and the performance of the matheuristic, we carried out extensive computational experiments. According to the numerical results, the use of drones can significantly reduce the makespan and the proposed VIEQ as well as the matheuristic approach have a significant contribution in solving the VRPD effectively.
机译:在这项工作中,我们有兴趣研究无人机的车辆路径问题(VRPD)。给定卡车车队,其中每辆卡车都载有给定数量的无人机,目标在于设计可行的路线和无人机操作,以便为所有客户提供服务并实现最小的制造期。我们将VRPD公式化为混合整数线性程序(MILP),可以通过任何标准的MILP求解器进行求解。此外,为了提高求解器的性能,我们引入了几组有效不等式(VIEQ)。由于求解器在处理大型实例时的性能有限,因此我们提出了一种数学方法,可以有效利用VRPD的问题结构。作为这种方法的整体,我们提出了无人机分配和调度问题(DASP),该问题在给定了卡车的现有路线的情况下,寻求了无人机的最佳分配和调度,以使工期最小化。在这种情况下,我们为DASP提出了两种MILP配方。为了评估最先进的求解器在解决VRPD的MILP公式中的性能,拟议VIEQ的优势以及数学性能,我们进行了广泛的计算实验。根据数值结果,无人驾驶飞机的使用可以显着降低制造周期,并且所提出的VIEQ以及数学方法对于有效解决VRPD具有重要贡献。

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