A Constant-Approximation Algorithm for Budgeted Sweep Coverage with Mobile Sensors

Wei Liang, Shaojie Tang, Zhao Zhang
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Abstract

In this paper, we present the first constant-approximation algorithm for {\em budgeted sweep coverage problem} (BSC). The BSC involves designing routes for a number of mobile sensors (a.k.a. robots) to periodically collect information as much as possible from points of interest (PoIs). To approach this problem, we propose to first examine the {\em multi-orienteering problem} (MOP). The MOP aims to find a set of $m$ vertex-disjoint paths that cover as many vertices as possible while adhering to a budget constraint $B$. We develop a constant-approximation algorithm for MOP and utilize it to achieve a constant-approximation for BSC. Our findings open new possibilities for optimizing mobile sensor deployments and related combinatorial optimization tasks.
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移动传感器预算扫面覆盖的常量近似算法
在本文中,我们首次提出了针对{预算清扫覆盖问题}(BSC)的常量近似算法。BSC 涉及为多个移动传感器(又称机器人)设计路线,以便定期从兴趣点(PoIs)收集尽可能多的信息。为了解决这个问题,我们建议首先研究{em multi-orienteering problem} (MOP)。该问题的目标是找到一组 $m$ 的顶点相交路径,在遵守预算约束 $B$ 的前提下尽可能多地覆盖顶点。我们为 MOP 开发了一种近似算法,并利用它实现了对 BSC 的近似。我们的发现为优化移动传感器部署和相关组合优化任务提供了新的可能性。
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