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On the Parameterized Complexity of Computing Graph Bisections

机译:关于计算图二等分的参数化复杂度

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The Bisection problem asks for a partition of the vertices of a graph into two equally sized sets, while minimizing the cut size. This is the number of edges connecting the two vertex sets. Bisection has been thoroughly studied in the past. However, only few results have been published that consider the parameterized complexity of this problem. We show that Bisection is FPT w.r.t. the minimum cut size if there is an optimum bisection that cuts into a given constant number of connected components. Our algorithm applies to the more general Balanced Biseparator problem where vertices need to be removed instead of edges. We prove that this problem is W-hard w.r.t. the minimum cut size and the number of cut out components. For Bisection we further show that no polynomial-size kernels exist for the cut size parameter. In fact, we show this for all parameters that are polynomial in the input size and that do not increase when taking disjoint unions of graphs. We prove fixed-parameter tractability for the distance to constant cliquewidth if we are given the deletion set. This implies fixed-parameter algorithms for some well-studied parameters such as cluster vertex deletion number and feedback vertex set.
机译:二等分问题要求将图的顶点划分为两个大小相等的集合,同时最大程度地减少剪切大小。这是连接两个顶点集的边数。过去一直对Bisection进行过深入的研究。但是,只有很少的结果发表过,考虑到此问题的参数化复杂性。我们证明Bisection是FPT w.r.t.如果有最佳的二等分线可以切成给定数量恒定的连接组件,则最小切割尺寸。我们的算法适用于更通用的平衡Biseparator问题,在该问题中需要删除顶点而不是边缘。我们证明这个问题是难以解决的最小裁切尺寸和裁切部件数量。对于Bisection,我们进一步表明,针对cut size参数,不存在多项式大小的内核。实际上,我们针对输入大小为多项式且在采用图的不相交并集时不会增加的所有参数显示此参数。如果给定了删除集,我们证明了到恒定群宽度的距离的固定参数易处理性。这意味着对一些经过充分研究的参数(例如簇顶点删除数和反馈顶点集)使用固定参数算法。

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