Parameterized complexity of dominating set variants in almost cluster and split graphs

IF 0.9 3区 计算机科学 Q1 BUSINESS, FINANCE
Dishant Goyal , Ashwin Jacob , Kaushtubh Kumar , Diptapriyo Majumdar , Venkatesh Raman
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引用次数: 0

Abstract

We consider structural parameterizations of several variants of Dominating Set in the parameter ecology program. We give improved FPT algorithms and lower bounds under well-known conjectures for Dominating Set and its variants in graphs that are k vertices away from a cluster graph or a split graph. These are graphs in which there is a set of k vertices (called the modulator) whose deletion results in a cluster graph or a split graph. We also call k as the deletion distance (to the appropriate class of graphs). For example, we show that when parameterized by the deletion distance k to cluster graphs: Dominating Set, Independent Dominating Set, Dominating Clique, Efficient Dominating Set and Total Dominating Set can be solved in 3knO(1)-time. Additionally, when parameterized by the deletion distance k to split graphs, we prove that Efficient Dominating Set can be solved in 3k/2nO(1)-time breaking the 2k barrier.
几乎聚类图和分裂图中支配集变量的参数化复杂度
研究了参数生态规划中支配集的几种变体的结构参数化问题。我们给出了改进的FPT算法和已知猜想下的支配集及其变体在离聚类图或分裂图有k个顶点的图中的下界。这些图中有一组k个顶点(称为调制器),删除这些顶点会产生聚类图或分割图。我们也称k为删除距离(到相应的图类)。例如,我们证明了当用删除距离k参数化聚类图时:支配集、独立支配集、支配团、有效支配集和总支配集可以在3knO(1)时间内求解。此外,当以分割图的删除距离k作为参数化时,我们证明了有效支配集可以在3k/2nO(1)时间内解决,打破了2k的障碍。
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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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