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An Effective Branching Strategy for Some Parameterized Edge Modification Problems with Multiple Forbidden Induced Subgraphs

机译:具有多个禁止诱导子图的某些参数化边缘修改问题的有效分支策略

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Branching on forbidden induced subgraphs is a genetic strategy to obtain parameterized algorithms for many edge modification problems. For such a problem in which the graph property is defined by multiple forbidden induced subgraphs, branching process is trivially performed on each subgraph. Thus, the size of the resulting search tree is dominated by the size of the largest forbidden subgraph. In this paper, we present a simple strategy for deriving significantly improved branching rules for dealing with multiple forbidden subgraphs by edge modifications. The basic idea hereby is that while constructing branching rules for the largest forbidden subgraph, we sufficiently take into account the structural relationship between it and other forbidden subgraphs. By applying this strategy, we obtain improved parameterized algorithms for edge modification problems for several graph properties such as proper interval, 3-leaf power, threshold and co-trivially perfect graphs.
机译:在禁止的诱导子图上分支是一种获得许多边缘修改问题的参数化算法的遗传策略。对于这样的问题,即其中的图形属性由多个禁止的诱导子图定义,在每个子图上琐碎地进行分支处理。因此,结果搜索树的大小由最大的禁止子图的大小决定。在本文中,我们提出了一种简单的策略,用于通过边缘修改来导出用于处理多个禁止子图的显着改进的分支规则。因此,基本思想是,在为最大的禁止子图构造分支规则时,我们充分考虑了它与其他禁止子图之间的结构关系。通过应用此策略,我们获得了针对几种图形属性(如适当的间隔,三叶功率,阈值和平凡完美图形)的边缘修改问题的改进参数化算法。

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