On the complexity of rainbow vertex colouring diametral path graphs

IF 0.9 3区 计算机科学 Q1 BUSINESS, FINANCE
Jakob Dyrseth , Paloma T. de Lima
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引用次数: 0

Abstract

Given a graph and a colouring of its vertices, a rainbow path is a path such that all its internal nodes are coloured distinctly. A graph is rainbow vertex-connected if between every pair of vertices there exists a rainbow path. We study the problem of deciding whether a graph can be coloured using k colours such that it is rainbow vertex-connected. Heggernes et al. (MFCS, 2018) conjectured that if every induced subgraph in G has a dominating diametral path, then G can always be rainbow coloured with diam(G)1 colours. We confirm their conjecture for chordal, bipartite and claw-free diametral path graphs. We complement these results by showing the conjecture does not hold without the condition on every induced subgraph. In this case, even though diam(G) colours are enough, it is NP-complete to determine whether a graph with a dominating diametral path of length three can be rainbow coloured with two colours.
关于彩虹顶点对直径路径图着色的复杂性
给定一个图形及其顶点的颜色,彩虹路径是这样一条路径,它的所有内部节点都有不同的颜色。如果在每一对顶点之间存在彩虹路径,则图是彩虹顶点连通的。我们研究了一个图是否可以用k种颜色着色,使得它是彩虹顶点连通的问题。Heggernes等人(MFCS, 2018)推测,如果G中的每个诱导子图都有一个主导直径路径,那么G总是可以用直径(G)−1的颜色呈现彩虹色。我们对弦、二部和无爪的径路图证实了他们的猜想。我们通过证明该猜想在每个诱导子图上都不成立来补充这些结果。在这种情况下,即使直径(G)的颜色就足够了,但要确定一个主要直径路径长度为3的图是否可以用两种颜色着色,这是np完全的。
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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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