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Fast Heuristics for Traveling Salesman Problems with Multiple Flying Sidekicks

机译:多次飞行侧面的推销员问题的快速启发式

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Speedy delivery of products is important for customers and the optimization of the last mile has particular challenges. In recent years drone-supported delivery has become increasingly feasible and therefore a topic of intense research. In this paper we address a traveling salesman problem where a truck has to serve customers and can use drones as flying sidekicks for the delivery of parcels. The goal is to assign customers to be either served by the truck or by some drone and schedule all events in order to minimize the total completion time of whole operation. We propose a heuristic for this problem, and introduce several novel components, including a multi-armed bandit selection for partitioning customers, an efficient matching-based heuristic for assigning drones to customers, local searches to improve solutions, and a fast greedy scheduler to estimate solution quality. In computational experiments we show that the combined approach finds better solutions than current methods, in less time.
机译:快速交付产品对客户很重要,最后一英里的优化具有特殊的挑战。近年来,无人机支持的交付变得越来越可行,因此是一个激烈的研究。在本文中,我们解决了一辆旅行的推销员问题,卡车必须为客户提供服务,并且可以使用无人机作为飞行侧面划分的包裹。目标是将客户指定为卡车或某些无人机服务,并安排所有事件以最小化整个操作的总完成时间。我们向这个问题提出了一个启发式,并介绍了几种新颖的组件,包括用于分配客户的多武装强盗选择,这是一种用于为客户分配无人机的有效匹配的启发式,以改善解决方案,以及快速贪婪的调度器来估计。解决方案质量。在计算实验中,我们表明,在更少的时间内,组合方法发现比当前方法更好的解决方案。

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