Subexponential algorithms for partial cover problems

  • Authors:

  • Fedor V. Fomin;Daniel Lokshtanov;Venkatesh Raman;Saket Saurabh

  • Affiliations:

  • Department of Informatics, University of Bergen, Norway;Department of CS and Engineering, University of California, San Diego, USA;The Institute of Mathematical Sciences, Chennai, India;The Institute of Mathematical Sciences, Chennai, India

  • Venue:
  • Information Processing Letters
  • Year:
  • 2011

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Abstract

Partial Cover problems are optimization versions of fundamental and well-studied problems like Vertex Cover and Dominating Set. Here one is interested in covering (or dominating) the maximum number of edges (or vertices) using a given number k of vertices, rather than covering all edges (or vertices). In general graphs, these problems are hard for parameterized complexity classes when parameterized by k. It was recently shown by Amini et al. (2008) [1] that Partial Vertex Cover and Partial Dominating Set are fixed parameter tractable on large classes of sparse graphs, namely H-minor-free graphs, which include planar graphs and graphs of bounded genus. In particular, it was shown that on planar graphs both problems can be solved in time 2^O^(^k^)n^O^(^1^). During the last decade there has been an extensive study on parameterized subexponential algorithms. In particular, it was shown that the classical Vertex Cover and Dominating Set problems can be solved in subexponential time on H-minor-free graphs. The techniques developed to obtain subexponential algorithms for classical problems do not apply to partial cover problems. It was left as an open problem by Amini et al. (2008) [1] whether there is a subexponential algorithm for Partial Vertex Cover and Partial Dominating Set. In this paper, we answer the question affirmatively by solving both problems in time 2^O^(^k^)n^O^(^1^) not only on planar graphs but also on much larger classes of graphs, namely, apex-minor-free graphs. Compared to previously known algorithms for these problems our algorithms are significantly faster and simpler.