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arXiv 1611.02002cs.DM
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上可比图的最大团结构及其应用

Maximal cliques structure for cocomparability graphs and applications

Jérémie Dusart, Michel Habib, Derek G. Corneil

摘要:

一个上可比较图是一个其补图允许传递定向的图。区间图是一族区间在实直线上的交图。本文研究了区间图与协可比图之间的关系。这项研究的动机是最近的结果Corneil,Dalton,Habib(2013)和Dusart,Habib(2016),这些结果表明,对于某些问题,在区间图上使用的算法也可以在协可比图上进行小的修改。这些算法中的许多都是基于图搜索,保持cocomparabilityordings。首先,我们提出了一个共同可比图通过其最大集团集上的格结构的特征。利用这个特征,我们可以证明协可比图$G$的每个最大区间子图也是$G$的最大弦子图。虽然这个最大团的格的大小可以是图的大小的指数,但它可以用作设计和证明协可比图算法的框架。特别是,我们表明,一个新的图形搜索,即本地最大邻域搜索(LocalMNS)导致$O(n+mlogn)$时间算法找到一个最大的间隔子图的协可比图。类似地,我们提出了一个线性时间算法来计算所有单纯顶点的协可比图。在这两种情况下,我们都在改进现有的知识。

英文摘要:

A cocomparability graph is a graph whose complement admits a transitive orientation. An interval graph is the intersection graph of a family of intervals on the real line. In this paper we investigate the relationships between interval and cocomparability graphs. This study is motivated by recent results Corneil,Dalton, Habib (2013) and Dusart, Habib (2016) and that show that for some problems, the algorithm used on interval graphs can also be used with small modifications on cocomparability graphs. Many of these algorithms are based on graph searches that preserve cocomparability orderings. First we propose a characterization of cocomparability graphs via a lattice structure on the set of their maximal cliques. Using this characterization we can prove that every maximal interval subgraph of a cocomparability graph $G$ is also a maximal chordal subgraph of $G$. Although the size of this lattice of maximal cliques can be exponential in the size of the graph, it can be used as a framework to design and prove algorithms on cocomparability graphs. In particular we show that a new graph search, namely Local Maximal Neighborhood Search (LocalMNS) leads to an $O(n+mlogn)$ time algorithm to find a maximal interval subgraph of a cocomparability graph. Similarly we propose a linear time algorithm to compute all simplicial vertices in a cocomparability graph. In both cases we improve on the current state of knowledge.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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