arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2012.00086cs.DSmath.OC
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弥合树和连接增强之间的差距:统一和更强的方法

Bridging the Gap Between Tree and Connectivity Augmentation: Unified and Stronger Approaches

Federica Cecchetto, Vera Traub, Rico Zenklusen

摘要:

我们考虑的连通性增强问题(CAP),在生存性网络设计领域的一个经典问题。它是关于以最便宜的方式将图的边连通性增加一个单位。更准确地说,给定一个$k$ -边连通图$G=(V,E)$和一组额外的边,任务是找到一个额外的边的最小基数子集,其添加到$G$使图$(k+1)$ -边连通。如果$k$是奇数,则已知该问题简化为树扩充问题(TAP)--即,$G$是一种生成树--最近在这方面取得了重大进展,导致逼近因子低于$1.5$(目前最好的因子是$1.458$)。然而,技术咨询方案的进展迄今没有结转到联合呼吁程序。事实上,直到最近,Byrka,Grandoni和Ameli(STOC 2020)通过提出一种基于与TAP最新进展不相交的方法的$1.91$ -近似算法,设法获得了CAP的$2$以下的第一近似因子。我们首先弥合TAP和CAP之间的差距,通过提出技术,允许利用TAP的见解和方法来接近CAP。然后,我们介绍了一种新的方法来获得逼近因子低于$1.5$,基于一种新的分析技术。通过这些成分,我们得到了一个$1.393$ -近似算法的CAP,因此也TAP。这导致了目前两个问题的最佳近似结果以统一的方式,通过显着改进上述CAP的$1.91$近似以及Grandoni,Kalaitzis和Zenklusen(STOC 2018)之前TAP的最佳近似因子$1.458$。此外,我们从最近的TAP进展继承的一个功能是,我们的方法可以处理的加权设置时,最大到最小的成本之间的比率在额外的链接是有界的,在这种情况下,我们得到的近似因子低于$1.5$。

英文摘要:

We consider the Connectivity Augmentation Problem (CAP), a classical problem in the area of Survivable Network Design. It is about increasing the edge-connectivity of a graph by one unit in the cheapest possible way. More precisely, given a $k$-edge-connected graph $G=(V,E)$ and a set of extra edges, the task is to find a minimum cardinality subset of extra edges whose addition to $G$ makes the graph $(k+1)$-edge-connected. If $k$ is odd, the problem is known to reduce to the Tree Augmentation Problem (TAP) -- i.e., $G$ is a spanning tree -- for which significant progress has been achieved recently, leading to approximation factors below $1.5$ (the currently best factor is $1.458$). However, advances on TAP did not carry over to CAP so far. Indeed, only very recently, Byrka, Grandoni, and Ameli (STOC 2020) managed to obtain the first approximation factor below $2$ for CAP by presenting a $1.91$-approximation algorithm based on a method that is disjoint from recent advances for TAP. We first bridge the gap between TAP and CAP, by presenting techniques that allow for leveraging insights and methods from TAP to approach CAP. We then introduce a new way to get approximation factors below $1.5$, based on a new analysis technique. Through these ingredients, we obtain a $1.393$-approximation algorithm for CAP, and therefore also TAP. This leads to the currently best approximation result for both problems in a unified way, by significantly improving on the above-mentioned $1.91$-approximation for CAP and also the previously best approximation factor of $1.458$ for TAP by Grandoni, Kalaitzis, and Zenklusen (STOC 2018). Additionally, a feature we inherit from recent TAP advances is that our approach can deal with the weighted setting when the ratio between the largest to smallest cost on extra links is bounded, in which case we obtain approximation factors below $1.5$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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