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On Structural Parameterizations of Happy Coloring, Empire Coloring and Boxicity

机译:关于快乐着色,帝国着色和适应性的结构参数化

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Distance parameters are extensively used to design efficient algorithms for many hard graph problems. They measure how far a graph is from belonging to some class of graphs. If a problem is tractable on a class of graphs then distances to j provide interesting parameterizations to that problem. For example, the parameter vertex cover measures the closeness of a graph to an edgeless graph. Many hard problems are tractable on graphs of small vertex cover. However, the parameter vertex cover is very restrictive in the sense that the class of graphs with bounded vertex cover is small. This significantly limits its usefulness in practical applications. In general, it is desirable to find tractable results for parameters such that the class of graphs with the parameter bounded should be as large as possible. In this spirit, we consider the parameter distance to threshold graphs, which are graphs that are both split graphs and cographs. It is a natural choice of an intermediate parameter between vertex cover and clique-width. In this paper, we give parameterized algorithms for some hard graph problems parameterized by the distance to threshold graphs. We show that Happy Coloring and Empire Coloring problems are fixed-parameter tractable when parameterized by the distance to threshold graphs. We also present an approximation algorithm to compute the Boxicity of a graph parameterized by the distance to threshold graphs.
机译:距离参数被广泛用于为许多硬图问题设计有效的算法。他们测量一个图与属于某类图的距离。如果问题在一类图上是可解决的,则到j的距离将为该问题提供有趣的参数化。例如,参数顶点覆盖范围可衡量图形与无边图形的接近程度。在小的顶点覆盖图上,许多难题是很容易解决的。但是,在有界顶点覆盖的图的类别很小的意义上,参数顶点覆盖是非常严格的。这极大地限制了其在实际应用中的实用性。通常,希望找到参数的易于处理的结果,以使带有参数有界的图的类别应尽可能大。本着这种精神,我们考虑到参数阈值图的距离,阈值图既是拆分图又是cograph。这是在顶点覆盖率和集团宽度之间的中间参数的自然选择。在本文中,我们给出了针对一些硬图问题的参数化算法,这些问题由到阈值图的距离来参数化。我们表明,当通过与阈值图的距离进行参数化时,“快乐着色”和“帝国着色”问题是固定参数可处理的。我们还提出了一种近似算法,用于计算由距离阈值图的距离参数化的图的Boxicity。

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