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Two echelon vehicle routing problem with drones in last mile delivery

机译:两个梯队车辆路由问题在最后一英里交付中的无人机

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摘要

In recent years, drone routing and scheduling has become a highly active area of research. This research introduces a new routing model that considers a synchronized truck-drone operation by allowing multiple drones to fly from a truck, serve one or multiple customers, and return to the same truck for a battery swap and package retrieval. The model addresses two levels (echelons) of delivery: primary truck routing from the main depot to serve assigned customers and secondary drone routing from the truck, which behaves like a moveable intermediate depot to serve other sets of customers. The model takes into account both trucks' and drones' capacities with the objective of finding optimal mutes of both trucks and drones that minimizes the total arrival time of both trucks and drones at the depot after completing the deliveries. The problem can be solved by formulated mixed integer programming (MIP) for the small-size problem, and two efficient heuristic algorithms are designed to solve the large-size problems: Drone Truck Route Construction (DTRC) and Large Neighborhood Search (LNS). Numeric results from the experiment compare the performance of both heuristics against the MIP method in small/medium-size instances from the literature. A sensitivity analysis is conducted to show the delivery time improvement of the proposed model over the previous truck-drone routing models.
机译:近年来,无人机路由和调度已成为一个高度活跃的研究领域。本研究介绍了一种新的路由模型,通过允许多个无人机从卡车飞行,服务一个或多个客户,并返回到电池交换和包裹检索的同一辆卡车,并将其返回同步的卡车 - 无人机操作。该模型解决了两个级别(梯队)的交货:主要车库的主要卡车路由为从卡车提供分配的客户和次级无人机路由,这表现得像一个可移动的中间仓库,以满足其他客户。该模型考虑了卡车'和无人机的能力,目的是找到一种卡车和无人机的最佳静音,这使得在完成交付后,可以最大限度地减少卡车和无人机的总到达时间。该问题可以通过配制混合整数编程(MIP)来解决小尺寸问题,并且旨在解决两个有效的启发式算法来解决大尺寸问题:无人机卡车路线施工(DTRC)和大型邻居搜索(LNS)。来自实验的数字结果比较了从文献中的小/中等实例中对MIP方法的启发式方法的性能。进行了灵敏度分析,以显示拟议模型在以前的卡车 - 无人机路由模型上的交货时间改进。

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