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arXiv 2107.07403cs.DSmath.OC
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加权树扩充和Steiner树的局部搜索

Local Search for Weighted Tree Augmentation and Steiner Tree

Vera Traub, Rico Zenklusen

摘要:

我们提出了一种技术,允许改善一些相对贪婪的程序精心挑选(非遗忘)的局部搜索算法。相对贪婪过程是一种特殊类型的贪心算法,它从一个简单但较弱的解开始,并迭代地用较强的分量替换该初始解的一部分。相对贪心算法的一些著名应用包括Steiner树的近似算法,以及最近的连通性增强问题。我们的技术的主要应用导致$(1.5+ε)$ -近似加权树增强,改进最近的相对贪婪的方法与近似因子$1+\ln 2 + ε\approx 1.69$。此外,我们展示了如何我们的本地搜索技术可以应用到斯坦纳树,导致另一种方法来获得目前最知名的近似因子的$\ln 4 + ε$。与以前的方法相反,我们的方法是纯粹的组合,而不需要解决LP。尽管如此,解决方案的价值仍然可以在著名的hypergraphic LP方面的限制,导致一个替代的,可以说是更简单的,技术来限制其完整性差距的$\ln 4$。

英文摘要:

We present a technique that allows for improving on some relative greedy procedures by well-chosen (non-oblivious) local search algorithms. Relative greedy procedures are a particular type of greedy algorithm that start with a simple, though weak, solution, and iteratively replace parts of this starting solution by stronger components. Some well-known applications of relative greedy algorithms include approximation algorithms for Steiner Tree and, more recently, for connectivity augmentation problems. The main application of our technique leads to a $(1.5+ε)$-approximation for Weighted Tree Augmentation, improving on a recent relative greedy based method with approximation factor $1+\ln 2 + ε\approx 1.69$. Furthermore, we show how our local search technique can be applied to Steiner Tree, leading to an alternative way to obtain the currently best known approximation factor of $\ln 4 + ε$. Contrary to prior methods, our approach is purely combinatorial without the need to solve an LP. Nevertheless, the solution value can still be bounded in terms of the well-known hypergraphic LP, leading to an alternative, and arguably simpler, technique to bound its integrality gap by $\ln 4$.

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