独立切集问题的精确算法和参数化算法

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE
Johannes Rauch , Dieter Rautenbach , Uéverton S. Souza
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引用次数: 0

摘要

独立切集问题问的是给定图形中是否存在既独立又是切集的顶点集合。即使输入图是平面图且最大阶数为 5,这个问题也是不完整的。我们首先提出了一种 O⁎(1.4423n)-时间算法来计算最小独立切集(如果有的话)。由于独立切集的性质是 MSO1 可表达的,我们的主要结果涉及问题的结构参数化,即考虑与 clique-width 不可比的参数。我们提出了以下参数下的-时间算法:最大度的对偶、解大小的对偶、支配集的大小(支配集作为额外输入给出)、奇循环横向的大小、与弦图的距离以及与无 P5 图的距离。最后,我们将介绍α支配的概念,它概括了本文的主要观点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exact and parameterized algorithms for the independent cutset problem
The Independent Cutset problem asks whether there is a set of vertices in a given graph that is both independent and a cutset. This problem is
-complete even when the input graph is planar and has maximum degree five. We first present a O(1.4423n)-time algorithm to compute a minimum independent cutset (if any). Since the property of having an independent cutset is MSO1-expressible, our main results are concerned with structural parameterizations for the problem considering parameters incomparable with clique-width. We present
-time algorithms under the following parameters: the dual of the maximum degree, the dual of the solution size, the size of a dominating set (where a dominating set is given as an additional input), the size of an odd cycle transversal, the distance to chordal graphs, and the distance to P5-free graphs. We close by introducing the notion of α-domination, which generalizes key ideas of this article.
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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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