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A New Truck-Drone Routing Problem for Parcel Delivery Services Aided by Parking Lots

机译:一个新的卡车 - 无人机路由问题,适用于停车场的包裹送货服务

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摘要

Collaborative routing aided by drones in last-mile delivery (LMD) has been an extensively studied topic in recent years. In this article, a new optimization problem for collaborative routing with a truck and a fleet of drones in LMD is introduced. The problem proposes a new strategy to coordinate a truck and a fleet of drones to serve a given set of customers. The plan is based on identifying the locations where the truck can park and where the drones fly to serve the customers. A procedure to locate these parking lots conveniently is given. For the transportation network, which includes these points, a mixed linear integer programming formulation is provided, which aims to minimize the makespan of serving all the customers. Computational experiments on a set of problem instances were conducted to analyze the model solutions’ characteristics and find their computational limits. The experiments showed that the proposed model could significantly improve the results obtained when only the truck delivers. Additionally, we propose a GRASP metaheuristic to solve instances of greater size. Its computational performance was studied when applied to a set of instances with different characteristics. The paper discusses some insights obtained from the computational experimentation and presents future research directions.
机译:近年来,在最后一英里交货(LMD)中辅助无人机的协作路由一直是一个广泛的研究主题。在本文中,介绍了一种新的优化问题,用于使用卡车和LMD中的卡车和一支无人机的协作路线。问题提出了一种新的策略,可以协调一辆卡车和一支无人机队伍为特定的客户提供服务。该计划是基于识别卡车可以停放的地点以及无人机飞向服务的地方。给出了方便地找到这些停车场的程序。对于包括这些点的运输网络,提供了一种混合线性整数编程配方,其目的是最大限度地减少为所有客户提供服务的Mapspan。进行了一组问题实例的计算实验,分析了模型解决方案的特征并找到了计算限制。实验表明,该模型可以显着改善仅当卡车提供时获得的结果。此外,我们提出了一种掌握成群质主义来解决更大尺寸的情况。当应用于具有不同特性的一组实例时,研究了其计算性能。本文讨论了从计算实验中获得的一些见解,并提出了未来的研究方向。

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