Exact and Approximate Drone Warehouse for a Mixed Landscape Delivery System

2019 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2019-06-01 DOI:10.1109/SMARTCOMP.2019.00062

Luca Bartoli, Francesco Betti Sorbelli, Federico Coró, M. C. Pinotti, Anil M. Shende

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引用次数: 8

Abstract

We introduce a drone delivery system for the "last-mile" logistics of small parcels. The system serves mixed delivery areas modeled as EMs. The shortest path between two destinations of an EM concatenates the Euclidean-and Manhattan-distance metrics. The drone's mission consists in one delivery for each destination of the grid, and, due to the strict payload constraint, the drone returns to the warehouse after each delivery. Our goal is to set the drone's warehouse in the delivery area so as the sum of the distances between the locations to be served and the warehouse is minimized. We exactly solve the problem proposing an algorithm that takes logarithmic time in the length of the Euclidean side of the EM. We also devise two approximate solutions that select the warehouse among a constant number of vertices of the EM. Such solutions are almost as good as the exact solution and we prove a √2-approximation bound in the worst case. Finally, we propose an exact solution for the two warehouse problem in a Manhattan grid, and an approximate solution for EMs.

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混合景观运输系统的精确和近似无人机仓库

我们为小包裹的“最后一英里”物流引入了无人机配送系统。系统服务于建模为EMs的混合交付区域。EM两个目的地之间的最短路径连接了欧几里得和曼哈顿距离度量。无人机的任务包括对网格的每个目的地进行一次交付，并且由于严格的有效载荷约束，无人机在每次交付后返回仓库。我们的目标是将无人机的仓库设置在送货区域，以便将服务地点与仓库之间的距离总和最小化。我们精确地解决了这个问题，提出了一种算法，该算法在EM的欧几里得侧的长度上花费对数时间。我们还设计了两个近似解，在EM的恒定数量的顶点中选择仓库。这样的解几乎和精确解一样好，我们在最坏的情况下证明了一个√2近似界。最后，我们提出了曼哈顿电网中两个仓库问题的精确解，以及EMs的近似解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 IEEE International Conference on Smart Computing (SMARTCOMP)

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