Improved approximation for tree augmentation: saving by rewiring

F. Grandoni, Christos Kalaitzis, R. Zenklusen
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引用次数: 37

Abstract

The Tree Augmentation Problem (TAP) is a fundamental network design problem in which we are given a tree and a set of additional edges, also called links. The task is to find a set of links, of minimum size, whose addition to the tree leads to a 2-edge-connected graph. A long line of results on TAP culminated in the previously best known approximation guarantee of 1.5 achieved by a combinatorial approach due to Kortsarz and Nutov [ACM Transactions on Algorithms 2016], and also by an SDP-based approach by Cheriyan and Gao [Algorithmica 2017]. Moreover, an elegant LP-based (1.5+є)-approximation has also been found very recently by Fiorini, Groß, K'onemann, and Sanitá [SODA 2018]. In this paper, we show that an approximation factor below 1.5 can be achieved, by presenting a 1.458-approximation that is based on several new techniques. By extending prior results of Adjiashvili [SODA 2017], we first present a black-box reduction to a very structured type of instance, which played a crucial role in recent development on the problem, and which we call k-wide. Our main contribution is a new approximation algorithm for O(1)-wide tree instances with approximation guarantee strictly below 1.458, based on one of their fundamental properties: wide trees naturally decompose into smaller subtrees with a constant number of leaves. Previous approaches in similar settings rounded each subtree independently and simply combined the obtained solutions. We show that additionally, when starting with a well-chosen LP, the combined solution can be improved through a new “rewiring” technique, showing that one can replace some pairs of used links by a single link. We can rephrase the rewiring problem as a stochastic version of a matching problem, which may be of independent interest. By showing that large matchings can be obtained in this problem, we obtain that a significant number of rewirings are possible, thus leading to an approximation factor below 1.5.
改进的树增强近似:通过重新布线节省
树增强问题(TAP)是一个基本的网络设计问题,其中我们给定一棵树和一组附加边,也称为链路。任务是找到一组最小尺寸的链接,将其添加到树中得到一个2边连通图。在TAP上的一长串结果最终达到了以前最著名的近似保证1.5,这是由Kortsarz和Nutov (ACM Transactions on Algorithms 2016)的组合方法实现的,也是由Cheriyan和Gao (Algorithmica 2017)的基于sdp的方法实现的。此外,Fiorini, Groß, K'onemann和sanit最近也发现了一个优雅的基于lp的(1.5+ n)近似[SODA 2018]。在本文中,我们表明,通过提出基于几种新技术的1.458近似值,可以实现低于1.5的近似因子。通过扩展Adjiashvili [SODA 2017]的先前结果,我们首先提出了一个非常结构化类型的实例的黑盒约简,它在问题的最近发展中起着至关重要的作用,我们称之为k-wide。我们的主要贡献是一种新的近似算法,用于O(1)宽的树实例,其近似保证严格低于1.458,基于它们的一个基本性质:宽树自然地分解成具有恒定数量叶子的更小的子树。在类似的情况下,以前的方法独立地对每个子树进行舍入,并简单地将得到的解组合起来。此外,我们表明,当从一个精心选择的LP开始时,可以通过一种新的“重新布线”技术来改进组合解决方案,表明可以用单个链路替换一些使用过的链路对。我们可以将重新布线问题重新表述为匹配问题的随机版本,这可能是独立的兴趣。通过展示在这个问题中可以获得大的匹配,我们得到大量的重接线是可能的,从而导致近似因子低于1.5。
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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