English

Smaller parameters for vertex cover kernelization

Data Structures and Algorithms 2017-11-15 v1 Computational Complexity

Abstract

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 O(X12)\mathcal{O}(|X|^{12}) vertices when XX is a vertex set such that each connected component of GXG-X contains at most one cycle, i.e., XX is a modulator to a pseudoforest. We strongly generalize this result by using modulators to dd-quasi-forests, i.e., graphs where each connected component has a feedback vertex set of size at most dd, and obtain kernels with O(X3d+9)\mathcal{O}(|X|^{3d+9}) vertices. Our result relies on proving that minimal blocking sets in a dd-quasi-forest have size at most d+2d+2. This bound is tight and there is a related lower bound of O(Xd+2ϵ)\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 dd-quasi-bipartite graphs, where each connected component can be made bipartite by deleting at most dd vertices, we get the same tight bound of d+2d+2 vertices. For graphs whose connected components each have a vertex cover of cost at most dd more than the best fractional vertex cover, which we call dd-quasi-integral, we show that minimal blocking sets have size at most 2d+22d+2, which is also tight. Combined with existing randomized polynomial kernelizations this leads to randomized polynomial kernelizations for modulators to dd-quasi-bipartite and dd-quasi-integral graphs. There are lower bounds of O(Xd+2ϵ)\mathcal{O}(|X|^{d+2-\epsilon}) and O(X2d+2ϵ)\mathcal{O}(|X|^{2d+2-\epsilon}) for the bit size of such kernels.

Keywords

Cite

@article{arxiv.1711.04604,
  title  = {Smaller parameters for vertex cover kernelization},
  author = {Eva-Maria C. Hols and Stefan Kratsch},
  journal= {arXiv preprint arXiv:1711.04604},
  year   = {2017}
}