弦图子类上不相交路径问题的核

IF 0.9 3区 计算机科学 Q1 BUSINESS, FINANCE
Juhi Chaudhary , Harmender Gahlawat , Michal Wlodarczyk , Meirav Zehavi
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引用次数: 0

摘要

给定一个无向图G和一个由k个端点对X组成的多集,顶点不相交路径()和边不相交路径()问题问的是G内部是否分别有k对顶点不相交路径和k对边不相交路径连接X上的每一个端点对。为此,我们在分割图上设计了一个4k顶点核,在良分割弦图上设计了一个O(k2)顶点核。我们还证明了问题在阈值图上是多项式时间可解的。对于EDP,我们首先证明了问题在完全图上是np完全的。然后,我们在分割图上设计了一个0 (k2.75)顶点核,并在阈值图上将其改进为7k+1顶点核。最后,我们为块图提供了一个O(k2)顶点核,为团路径提供了一个2k+1顶点核。我们的贡献改进了文献中的几个结果,并解决了Heggernes等人(2015)提出的一个悬而未决的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kernels for the Disjoint Paths Problem on Subclasses of Chordal Graphs
Given an undirected graph G and a multiset of k terminal pairs X, the Vertex-Disjoint Paths (
) and Edge-Disjoint Paths (
) problems ask whether G has k pairwise internally vertex-disjoint paths and k pairwise edge-disjoint paths, respectively, connecting every terminal pair in X. In this paper, we study the kernelization complexity of
and
on subclasses of chordal graphs. For
, we design a 4k vertex kernel on split graphs and an O(k2) vertex kernel on well-partitioned chordal graphs. We also show that the problem becomes polynomial-time solvable on threshold graphs. For EDP, we first prove that the problem is NP-complete on complete graphs. Then, we design an O(k2.75) vertex kernel for
on split graphs, and improve it to a 7k+1 vertex kernel on threshold graphs. Lastly, we provide an O(k2) vertex kernel for
on block graphs and a 2k+1 vertex kernel for clique paths. Our contributions improve upon several results in the literature, as well as resolve an open question by Heggernes et al. (2015) [27].
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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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