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首页> 外文期刊>Journal of combinatorial optimization >An effective branching strategy based on structural relationship among multiple forbidden induced subgraphs
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An effective branching strategy based on structural relationship among multiple forbidden induced subgraphs

机译:基于多个禁止诱导子图之间结构关系的有效分支策略

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摘要

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 to deal 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 3-leaf power, proper interval, 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,可通过边缘修改来导出显着改善的分支规则,以处理多个禁止的子图。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,我们获得了针对改进的参数化算法,以解决多个图属性(例如3叶幂,适当间隔,阈值和共同平凡图)的边缘修改问题。

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