Diminishable parameterized problems and strict polynomial kernelization

  • Henning Fernau
  • , Till Fluschnik
  • , Danny Hermelin
  • , Andreas Krebs
  • , Hendrik Molter
  • , Rolf Niedermeier

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Kernelization—a mathematical key concept for provably effective polynomial-time preprocessing of NP-hard problems—plays a central role in parameterized complexity and has triggered an extensive line of research. In this paper we consider a restricted yet natural variant of kernelization, namely strict kernelization, where one is not allowed to increase the parameter of the reduced instance (the kernel) by more than an additive constant. Building on earlier work of Chen, Flum, and Müller [CiE 2009, Theory Comput. Syst. 2011], we underline the applicability of their framework by showing that a variety of fixed-parameter tractable problems, including graph problems and Turing machine computation problems, does not admit strict polynomial kernels under the weaker assumption of P ≠ NP. Finally, we study a relaxation of the notion of strict kernels.

Original languageEnglish
Title of host publicationSailing Routes in the World of Computation - 14th Conference on Computability in Europe, CiE 2018, Proceedings
EditorsRussell G. Miller, Florin Manea, Dirk Nowotka
PublisherSpringer Verlag
Pages161-171
Number of pages11
ISBN (Print)9783319944173
DOIs
StatePublished - 1 Jan 2018
Event14th Conference on Computability in Europe, CiE 2018 - Kiel, Germany
Duration: 30 Jul 20183 Aug 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10936 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th Conference on Computability in Europe, CiE 2018
Country/TerritoryGermany
CityKiel
Period30/07/183/08/18

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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