Deletion to scattered graph classes II - improved FPT algorithms for deletion to pairs of graph classes

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE
Ashwin Jacob , Diptapriyo Majumdar , Venkatesh Raman
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引用次数: 2

Abstract

The problem of deletion of vertices to a hereditary graph class is a well-studied problem in parameterized complexity. Recently, a natural extension of the problem was initiated where we are given a finite set of hereditary graph classes and we determine whether k vertices can be deleted from a given graph so that the connected components of the resulting graph belong to one of the given hereditary graph classes. The problem is shown to be fixed parameter tractable (FPT) when the deletion problem to each of the given hereditary graph classes is fixed-parameter tractable, and the property of being in any of the graph classes is expressible in the counting monodic second order (CMSO) logic. This paper focuses on pairs of specific graph classes (Π1,Π2) in which we would like the connected components of the resulting graph to belong to, and design simpler and more efficient FPT algorithms.

对分散图类的删除II -改进的FPT算法对图类的删除
遗传图类的顶点删除问题是参数化复杂度中一个研究得很好的问题。最近,该问题的一个自然扩展被提出,其中我们得到了一组有限的遗传图类,并且我们确定是否可以从给定的图中删除k个顶点,使得得到的图的连接分量属于给定的遗传图类别之一。当每个给定的遗传图类的删除问题都是固定参数可处理的,并且在任何一个图类中的性质都可以用计数二阶(CMSO)逻辑表示时,该问题被证明是固定参数易处理的(FPT)。本文重点研究了一对特定的图类(π1,π2),我们希望得到的图的连通分量属于这些图类,并设计了更简单、更有效的FPT算法。
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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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