arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1907.04585cs.DScs.DM
收藏

H-自由图中最大权重独立集问题的拟多项式时间近似方案

Quasi-polynomial time approximation schemes for the Maximum Weight Independent Set Problem in H-free graphs

Maria Chudnovsky, Marcin Pilipczuk, Michał Pilipczuk, Stéphan Thomassé

AI总结:

本文针对H-自由图中的最大权重独立集问题,在H不含环、高度数顶点等困难结构时,提出了拟多项式时间近似方案和亚指数时间精确算法,并支持加权情形。

摘要:

在最大独立集问题中,我们需要在给定图中找到一个由两两不相邻的顶点组成的集合,并使其基数尽可能大。在一般图中,这个经典问题已知是NP困难的,并且对于任意ε>0,难以在n^{1-ε}的因子内近似。因此,研究最大独立集在各种图类中的复杂性,以期获得更好的可解性结果,是一个活跃的研究方向。在H-自由图(即不包含固定图H作为导出子图的图)中,当H包含一个环、一个度数至少为4的顶点,或在一个连通分量中包含两个度数至少为3的顶点时,该问题已知仍然是NP困难和APX困难的。对于其余情况,即H的每个分量都是路径或细分爪时,最大独立集的复杂性仍然广泛开放,仅有少数针对小图H(如P_5、P_6、爪或叉)的多项式时间可解结果。我们证明,对于每一个在H-自由图中最大独立集未知为APX困难和SUBEXP困难的图H,该问题在此图类中承认一个拟多项式时间近似方案和一个亚指数时间精确算法。我们的算法也适用于更一般的加权设置,其中输入图配有顶点上的权重函数,我们最大化独立集的总权重。

英文摘要:

In the Maximum Independent Set problem we are asked to find a set of pairwise nonadjacent vertices in a given graph with the maximum possible cardinality. In general graphs, this classical problem is known to be NP-hard and hard to approximate within a factor of $n^{1-\varepsilon}$ for any $\varepsilon > 0$. Due to this, investigating the complexity of Maximum Independent Set in various graph classes in hope of finding better tractability results is an active research direction. In $H$-free graphs, that is, graphs not containing a fixed graph $H$ as an induced subgraph, the problem is known to remain NP-hard and APX-hard whenever $H$ contains a cycle, a vertex of degree at least four, or two vertices of degree at least three in one connected component. For the remaining cases, where every component of $H$ is a path or a subdivided claw, the complexity of Maximum Independent Set remains widely open, with only a handful of polynomial-time solvability results for small graphs $H$ such as $P_5$, $P_6$, the claw, or the fork. We show that for every graph $H$ for which Maximum Independent Set is not known to be APX-hard and SUBEXP-hard in $H$-free graphs, the problem admits a quasi-polynomial time approximation scheme and a subexponential-time exact algorithm in this graph class. Our algorithm works also in the more general weighted setting, where the input graph is supplied with a weight function on vertices and we are maximizing the total weight of an independent set.

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。

↑