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oai:drops-oai.dagstuhl.de:1851 2024-03-06T10:33:14Z ddc:004 open_access

Polynomial Kernelizations for MIN F^+Pi_1 and MAX NP Kratsch, Stefan Parameterized complexity Kernelization Approximation algorithms 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~$\textsc{MIN F}^+\Pi_1$ and~$\textsc{MAX NP}$, including the well-known subclass~$\textsc{MAX SNP}$, 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~$\textsc{MAX SNP}$ and~$\textsc{MIN F}^+\Pi_1$ are fixed-parameter tractable, and complements recent research on problems that do not admit polynomial kernelizations (Bodlaender et al.\ ICALP 2008). Schloss Dagstuhl – Leibniz-Zentrum für Informatik Stefan Kratsch 2009 Is Part Of LIPIcs, Volume 3, 26th International Symposium on Theoretical Aspects of Computer Science (2009) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.STACS.2009.1851 urn:nbn:de:0030-drops-18511 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2009.1851 eng https://creativecommons.org/licenses/by-nd/3.0/legalcode