无四色[数学]图。II.寻找优秀的预着色

IF 1.2 3区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS SIAM Journal on Computing Pub Date : 2024-02-28 DOI:10.1137/18m1234849
Maria Chudnovsky, Sophie Spirkl, Mingxian Zhong
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引用次数: 0

摘要

SIAM 计算期刊》,第 53 卷第 1 期,第 146-187 页,2024 年 2 月。 摘要本文是两篇系列论文中的第二篇。该系列论文的目标是给出一种多项式时间算法,用于解决仅限于无诱导六顶点路径的图类的四着色问题和四预着色扩展问题,从而证明黄的一个猜想。结合之前已知的结果,这就完成了对具有连通禁止诱导子图的图的 4-着色问题复杂性的分类。在本文中,我们给出了一种多项式时间算法,它从一个没有六顶点路径的图的 4-预着色开始,输出一个多项式大小的所谓优秀预着色集合。优秀预着色比一般预着色更容易处理,此外,为了确定初始预着色是否可以扩展到整个图,只需回答集合中每个优秀预着色的相同问题即可。本系列的第一篇论文讨论了优秀的预着色,从而提供了问题的完整解决方案。
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Four-Coloring [math]-Free Graphs. II. Finding an Excellent Precoloring
SIAM Journal on Computing, Volume 53, Issue 1, Page 146-187, February 2024.
Abstract. This is the second paper in a series of two. The goal of the series is to give a polynomial-time algorithm for the 4-coloring problem and the 4-precoloring extension problem restricted to the class of graphs with no induced six-vertex path, thus proving a conjecture of Huang. Combined with previously known results, this completes the classification of the complexity of the 4-coloring problem for graphs with a connected forbidden induced subgraph. In this paper we give a polynomial time-algorithm that starts with a 4-precoloring of a graph with no induced six-vertex path and outputs a polynomial-sized collection of so-called excellent precolorings. Excellent precolorings are easier to handle than general ones, and, in addition, in order to determine whether the initial precoloring can be extended to the whole graph, it is enough to answer the same question for each of the excellent precolorings in the collection. The first paper in the series deals with excellent precolorings, thus providing a complete solution to the problem.
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来源期刊
SIAM Journal on Computing
SIAM Journal on Computing 工程技术-计算机:理论方法
CiteScore
4.60
自引率
0.00%
发文量
68
审稿时长
6-12 weeks
期刊介绍: The SIAM Journal on Computing aims to provide coverage of the most significant work going on in the mathematical and formal aspects of computer science and nonnumerical computing. Submissions must be clearly written and make a significant technical contribution. Topics include but are not limited to analysis and design of algorithms, algorithmic game theory, data structures, computational complexity, computational algebra, computational aspects of combinatorics and graph theory, computational biology, computational geometry, computational robotics, the mathematical aspects of programming languages, artificial intelligence, computational learning, databases, information retrieval, cryptography, networks, distributed computing, parallel algorithms, and computer architecture.
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