Approximation Algorithms for Steiner Tree Augmentation Problems

R. Ravi, Weizhong Zhang, Michael Zlatin
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引用次数: 1

Abstract

In the Steiner Tree Augmentation Problem (STAP), we are given a graph $G = (V,E)$, a set of terminals $R \subseteq V$, and a Steiner tree $T$ spanning $R$. The edges $L := E \setminus E(T)$ are called links and have non-negative costs. The goal is to augment $T$ by adding a minimum cost set of links, so that there are 2 edge-disjoint paths between each pair of vertices in $R$. This problem is a special case of the Survivable Network Design Problem, which can be approximated to within a factor of 2 using iterative rounding~\cite{J2001}. We give the first polynomial time algorithm for STAP with approximation ratio better than 2. In particular, we achieve an approximation ratio of $(1.5 + \varepsilon)$. To do this, we employ the Local Search approach of~\cite{TZ2022} for the Tree Augmentation Problem and generalize their main decomposition theorem from links (of size two) to hyper-links. We also consider the Node-Weighted Steiner Tree Augmentation Problem (NW-STAP) in which the non-terminal nodes have non-negative costs. We seek a cheapest subset $S \subseteq V \setminus R$ so that $G[R \cup S]$ is 2-edge-connected. Using a result of Nutov~\cite{N2010}, there exists an $O(\log |R|)$-approximation for this problem. We provide an $O(\log^2 (|R|))$-approximation algorithm for NW-STAP using a greedy algorithm leveraging the spider decomposition of optimal solutions.
Steiner树增广问题的近似算法
在斯坦纳树增强问题(STAP)中,我们给出了一个图$G = (V,E)$,一组终端$R \subseteq V$,以及一个斯坦纳树$T$生成$R$。这些边$L := E \setminus E(T)$被称为链接,它们的代价是非负的。我们的目标是通过添加一个最小代价的链接集来增强$T$,这样在$R$的每对顶点之间就有2条不相交的路径。这个问题是可生存网络设计问题的一个特殊情况,它可以使用迭代舍入\cite{J2001}在因子2内近似。给出了第一个近似比大于2的多项式时间算法。特别地,我们得到了近似的比值$(1.5 + \varepsilon)$。为了做到这一点,我们对树增强问题采用了\cite{TZ2022}的局部搜索方法,并将它们的主要分解定理从链接(大小为2)推广到超链接。我们还考虑了节点加权斯坦纳树增强问题(NW-STAP),其中非终端节点具有非负成本。我们寻找一个最便宜的子集$S \subseteq V \setminus R$,使得$G[R \cup S]$是2边连接的。利用Nutov \cite{N2010}的结果,这个问题存在一个$O(\log |R|)$ -近似。我们使用贪婪算法利用最优解的蜘蛛分解为NW-STAP提供了$O(\log^2 (|R|))$ -逼近算法。
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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CiteScore
6.50
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