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Polynomial Kernelizations for MIN F+PI 1 and MAX NP

Abstract : The relation of constant-factor approximability to fixed-parameter tractability and kernelization is a long-standing open question. We prove that two large classes of constant-factor approximable problems, namely~$\MINF_1$ and~$\MNP$, including the well-known subclass~$\MSNP$, admit polynomial kernelizations for their natural decision versions. This extends results of Cai and Chen (JCSS 1997), stating that the standard parameterizations of problems in~$\MSNP$ and~$\MINF_1$ are fixed-parameter tractable, and complements recent research on problems that do not admit polynomial kernelizations (Bodlaender et al.\ ICALP 2008).
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Submitted on : Tuesday, February 10, 2009 - 4:39:44 PM
Last modification on : Thursday, September 20, 2018 - 7:54:02 AM
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  • HAL Id : inria-00360229, version 1
  • ARXIV : 0902.1835



Stefan Kratsch. Polynomial Kernelizations for MIN F+PI 1 and MAX NP. 26th International Symposium on Theoretical Aspects of Computer Science STACS 2009, Feb 2009, Freiburg, Germany. pp.601-612. ⟨inria-00360229⟩



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