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The traveling salesman problem with release dates and drone resupply

机译:释放日期和无人机的旅行推销员问题再补给

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This paper introduces the Traveling Salesman Problem with Release Dates and Drone Resupply, which consists of finding a minimum time route for a single truck that can receive newly available orders en route via a drone sent from the depot. We assume that each order's release date is known at the time of delivery planning. This context is common for many applications, notably last-mile logistics. We develop a Mixed-Integer Linear Program and a solution approach for larger instances based on decomposing the problem into the truck-routing and the drone-resupply decisions. Numerical experiments show that using drones for resupply can reduce the total delivery time by up to 20%. Additionally, experiments show that the decomposition can rapidly obtain high-quality solutions. For instances of 10 and 15 customers, the decomposition solved the majority to optimality, with a trivial gap. For larger instances, this approach provided lower delivery times than a traditional parcel delivery system using a truck only. Investigations on the effects of drone speed, drone capacity, depot location, constraint addition, and allowing the truck to return to the depot are studied. We consider instances up to 50 customers. (C) 2020 Elsevier Ltd. All rights reserved.
机译:本文介绍了释放日期和无人机补给的旅行推销员问题,其中包括找到一个可通过从仓库发送的无人机接收新可用订单的单个卡车的最小时间路线。我们假设每个订单的发布日期在交付规划时已知。这种上下文对于许多应用程序很常见,特别是最后一英里的物流。我们基于将问题分解为卡车路由和无人机补给决策,我们开发混合整数线性程序和较大实例的解决方案方法。数值实验表明,使用无人机补给可以将总递送时间降低到20%。另外,实验表明,分解可以快速获得高质量的解决方案。对于10和15顾客的实例,分解解决了大多数最优,具有微不足道的差距。对于较大的实例,这种方法提供了比使用卡车的传统包裹递送系统更低的交货时间。研究了对无人机速度,无人机容量,仓库位置,约束加成以及允许卡车返回仓库的影响的研究。我们考虑高达50个客户的实例。 (c)2020 elestvier有限公司保留所有权利。

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