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arXiv 1502.00716cs.DS
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树分解上r-控制问题的最优动态规划

Optimal dynamic program for r-domination problems over tree decompositions

Glencora Borradaile, Hung Le

摘要:

在强指数时间假设(SETH)下,求解NP难问题的动态规划算法对树宽的指数依赖性是最优的。我们将这项工作扩展到$r$ -支配问题。在$r$ -支配集,人们希望找到一个顶点的最小子集$S$,使得$G$的每个顶点都在$S$中某个顶点的$r$跳数内.在连通$r$ -支配集中,还要求该集导出$G$的连通子图.给出了树宽$\mathrm{tw}$的$n$ -顶点图中$r$ -支配集的$O((2r+1)^{\mathrm{tw}} n)$时间算法和连通$r$ -支配集的$O((2r+2)^{\mathrm{tw}} n^{O(1)})$时间算法.我们表明,$r$和$\mathrm{tw}$的运行时间依赖性是最好的SETH下。这增加了先前的观察结果,即连接性约束需要分母中的“+1”。

英文摘要:

There has been recent progress in showing that the exponential dependence on treewidth in dynamic programming algorithms for solving NP-hard problems are optimal under the Strong Exponential Time Hypothesis (SETH). We extend this work to $r$-domination problems. In $r$-dominating set, one wished to find a minimum subset $S$ of vertices such that every vertex of $G$ is within $r$ hops of some vertex in $S$. In connected $r$-dominating set, one additionally requires that the set induces a connected subgraph of $G$. We give a $O((2r+1)^{\mathrm{tw}} n)$ time algorithm for $r$-dominating set and a $O((2r+2)^{\mathrm{tw}} n^{O(1)})$ time algorithm for connected $r$-dominating set in $n$-vertex graphs of treewidth $\mathrm{tw}$. We show that the running time dependence on $r$ and $\mathrm{tw}$ is the best possible under SETH. This adds to earlier observations that a "+1" in the denominator is required for connectivity constraints.

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