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Maximum common induced subgraph parameterized by vertex cover

机译:顶点覆盖参数化的最大公共感应子图

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The Maximum Common Induced Subgraph problem (MCIS) takes a pair of graphs as input and asks for a graph of maximum order that is isomorphic to an induced subgraph of each of the input graphs. The problem is NP-hard in general, and remains so on many graph classes including graphs of bounded treewidth. In the framework of parameterized complexity, the latter assertion means that MCIS is W-hard when parameterized by the treewidths of input graphs. A classical graph parameter that has been used recently in many parameterization problems is Vertex Cover. In this paper we prove constructively that MCIS is fixed-parameter tractable when parameterized by the vertex cover numbers of the input graphs. Our algorithm is also an improved exact algorithm for the problem on instances where the minimum vertex cover is small compared to the order of input graphs.
机译:最大共同诱导子图问题(MCIS)将一对图作为输入,并要求与每个输入图的诱导子图同构的最大阶图。这个问题一般来说都是NP难题,在许多图类(包括有界树宽图)中仍然存在。在参数化复杂度的框架中,后一个断言意味着当通过输入图的树宽进行参数化时,MCIS是W-hard的。最近在许多参数化问题中使用的经典图形参数是“顶点覆盖”。在本文中,我们通过结构性证明,当通过输入图的顶点覆盖号进行参数化时,MCIS是固定参数可处理的。对于与输入图的顺序相比最小顶点覆盖较小的情况,我们的算法也是针对该问题的改进的精确算法。

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