较小的参数用于顶点覆盖核化

Eva-Maria C. Hols, Stefan Kratsch
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引用次数: 12

摘要

我们重新讨论了相对于结构参数的顶点覆盖的多项式核问题。我们的起点是最近由Fomin和Str{\o}mme [WG 2016]发表的一篇论文,他们给出了一个具有$\mathcal{o} (|X|^{12})$顶点的核,当$X$是一个顶点集,使得$G-X$的每个连通分量最多包含一个循环,即$X$是伪森林的调制器。我们使用调制器将这一结果强推广到$d$-拟森林,即每个连通分量有一个最大$d$大小的反馈顶点集的图,并获得具有$\mathcal{O}(|X|^{3d+9})$顶点的核。我们的结果依赖于证明$d$-准森林中的最小块集的大小不超过$d+2$。这个边界很紧,并且在核的位大小上有一个相关的下界$\mathcal{O}(|X|^{d+2-\epsilon})$。事实上,我们也得到了更一般图类的最小块集的界:对于$d$-拟二部图,其中每个连通的分量可以通过删除最多$d$顶点而成为二部图,我们得到了$d+2$顶点的相同紧界。对于每个连通分量的顶点覆盖的代价最多$d$大于最佳分数顶点覆盖(我们称之为$d$-拟积分)的图,我们证明了最小块集的大小最多为$2d+2$,这也是紧的。结合已有的随机多项式核化方法,得到了d$-拟二部图和d$-拟积分图的调制器的随机多项式核化。对于这种核的位大小,有$\mathcal{O}(|X|^{d+2-\epsilon})$和$\mathcal{O}(|X|^{2d+2-\epsilon})$的下界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smaller parameters for vertex cover kernelization
We revisit the topic of polynomial kernels for Vertex Cover relative to structural parameters. Our starting point is a recent paper due to Fomin and Str{\o}mme [WG 2016] who gave a kernel with $\mathcal{O}(|X|^{12})$ vertices when $X$ is a vertex set such that each connected component of $G-X$ contains at most one cycle, i.e., $X$ is a modulator to a pseudoforest. We strongly generalize this result by using modulators to $d$-quasi-forests, i.e., graphs where each connected component has a feedback vertex set of size at most $d$, and obtain kernels with $\mathcal{O}(|X|^{3d+9})$ vertices. Our result relies on proving that minimal blocking sets in a $d$-quasi-forest have size at most $d+2$. This bound is tight and there is a related lower bound of $\mathcal{O}(|X|^{d+2-\epsilon})$ on the bit size of kernels. In fact, we also get bounds for minimal blocking sets of more general graph classes: For $d$-quasi-bipartite graphs, where each connected component can be made bipartite by deleting at most $d$ vertices, we get the same tight bound of $d+2$ vertices. For graphs whose connected components each have a vertex cover of cost at most $d$ more than the best fractional vertex cover, which we call $d$-quasi-integral, we show that minimal blocking sets have size at most $2d+2$, which is also tight. Combined with existing randomized polynomial kernelizations this leads to randomized polynomial kernelizations for modulators to $d$-quasi-bipartite and $d$-quasi-integral graphs. There are lower bounds of $\mathcal{O}(|X|^{d+2-\epsilon})$ and $\mathcal{O}(|X|^{2d+2-\epsilon})$ for the bit size of such kernels.
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