New Algorithms for Mixed Dominating Set

L. Dublois, M. Lampis, V. Paschos
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引用次数: 2

Abstract

A mixed dominating set is a collection of vertices and edges that dominates all vertices and edges of a graph.We study the complexity of exact and parameterized algorithms for MDS, resolving some open questions. In particular, we settle the problem's complexity parameterized by treewidth and pathwidth by giving an algorithm running in time $O^*(5^{tw})$ (improving the current best $O^*(6^{tw})$), as well as a lower bound showing that our algorithm cannot be improved under the SETH, even if parameterized by pathwidth (improving a lower bound of $O^*((2 - \varepsilon)^{pw})$). Furthermore, by using a simple but so far overlooked observation on the structure of minimal solutions, we obtain branching algorithms which improve both the best known FPT algorithm for this problem, from $O^*(4.172^k)$ to $O^*(3.510^k)$, and the best known exponential-time exact algorithm, from $O^*(2^n)$ and exponential space, to $O^*(1.912^n)$ and polynomial space.
混合支配集的新算法
混合支配集是支配图中所有顶点和边的顶点和边的集合。我们研究了精确算法和参数化算法的复杂性,解决了一些悬而未决的问题。特别地,我们通过给出一个运行时间$O^*(5^{tw})$的算法(改进了当前最好的$O^*(6^{tw})$)来解决由树宽和路径宽度参数化的问题的复杂性,并给出了一个下界,表明即使用路径宽度参数化(改进了$O^*((2 - \varepsilon)^{pw})$),我们的算法在SETH下也不能改进。此外,通过对最小解结构的一个简单但迄今为止被忽视的观察,我们得到了分支算法,它改进了该问题最著名的FPT算法,从$O^*(4.172^k)$到$O^*(3.510^k)$,以及最著名的指数时间精确算法,从$O^*(2^n)$和指数空间,到$O^*(1.912^n)$和多项式空间。
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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