Directed Subset Feedback Vertex Set is Fixed-Parameter Tractable
Abstract
Given a graph and an integer , the Feedback Vertex Set (FVS) problem asks if there is a vertex set of size at most that hits all cycles in the graph. The fixed-parameter tractability status of FVS in directed graphs was a long-standing open problem until Chen et al. (STOC '08) showed that it is FPT by giving a time algorithm. In the subset versions of this problems, we are given an additional subset of vertices (resp., edges) and we want to hit all cycles passing through a vertex of (resp. an edge of ). Recently, the Subset Feedback Vertex Set in undirected graphs was shown to be FPT by Cygan et al. (ICALP '11) and independently by Kakimura et al. (SODA '12). We generalize the result of Chen et al. (STOC '08) by showing that Subset Feedback Vertex Set in directed graphs can be solved in time . By our result, we complete the picture for feedback vertex set problems and their subset versions in undirected and directed graphs. Besides proving the fixed-parameter tractability of Directed Subset Feedback Vertex Set, we reformulate the random sampling of important separators technique in an abstract way that can be used for a general family of transversal problems. Moreover, we modify the probability distribution used in the technique to achieve better running time; in particular, this gives an improvement from to in the parameter dependence of the Directed Multiway Cut algorithm of Chitnis et al. (SODA '12).
Cite
@article{arxiv.1205.1271,
title = {Directed Subset Feedback Vertex Set is Fixed-Parameter Tractable},
author = {Rajesh Chitnis and Marek Cygan and MohammadTaghi Hajiaghayi and Dániel Marx},
journal= {arXiv preprint arXiv:1205.1271},
year = {2014}
}
Comments
To appear in ACM Transactions on Algorithms. A preliminary version appeared in ICALP '12. We would like to thank Marcin Pilipczuk for pointing out a missing case in the conference version which has been considered in this version. Also, we give an single exponential FPT algorithm improving on the double exponential algorithm from the conference version