English

On Algorithms for $L$-bounded Cut Problem

Data Structures and Algorithms 2017-09-11 v2

Abstract

Given a graph G=(V,E)G=(V,E) with two distinguished vertices s,tVs,t\in V and an integer parameter L>0L>0, an {\em LL-bounded cut} is a subset FF of edges (vertices) such that the every path between ss and tt in GFG\setminus F has length more than LL. The task is to find an LL-bounded cut of minimum cardinality. Though the problem is very simple to state and has been studied since the beginning of the 70's, it is not much understood yet. The problem is known to be NP\cal{NP}-hard to approximate within a small constant factor even for L4L\geq 4 (for L5L\geq 5 for the vertex cuts). On the other hand, the best known approximation algorithm for general graphs has approximation ratio only O(n2/3)\mathcal{O}({n^{2/3}}) in the edge case, and O(n)\mathcal{O}({\sqrt{n}}) in the vertex case, where nn denotes the number of vertices. We show that for planar graphs, it is possible to solve both the edge- and the vertex-version of the problem optimally in time O(L3Ln)\mathcal{O}(L^{3L}n). That is, the problem is fixed parameter tractable (FPT) with respect to LL on planar graphs. Furthermore, we show that the problem remains FPT even for bounded genus graphs, a super class of planar graphs. Our second contribution deals with approximations of the vertex version of the problem. We describe an algorithm that for a given a graph GG, its tree decomposition of treewidth τ\tau and vertices ss and tt computes a τ\tau-approximation of the minimum LL-bounded sts-t vertex cut; if the decomposition is not given, then the approximation ratio is O(τlogτ)\mathcal{O}(\tau \sqrt{\log \tau}). For graphs with treewidth bounded by O(n1/2ϵ)\mathcal{O}(n^{1/2-\epsilon}) for any ϵ>0\epsilon>0, but not by a constant, this is the best approximation in terms of~nn that we are aware of.

Keywords

Cite

@article{arxiv.1705.02390,
  title  = {On Algorithms for $L$-bounded Cut Problem},
  author = {Petr Kolman},
  journal= {arXiv preprint arXiv:1705.02390},
  year   = {2017}
}

Comments

11 pages + 2 pages of Appendix. The new version (Sep 8, 2017) improves by a logarithmic factor the approximation ratio in Section 3