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Kernelization: New Upper and Lower Bound Techniques

  • Hans L. Bodlaender
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5917)

Abstract

In this survey, we look at kernelization: algorithms that transform in polynomial time an input to a problem to an equivalent input, whose size is bounded by a function of a parameter. Several results of recent research on kernelization are mentioned. This survey looks at some recent results where a general technique shows the existence of kernelization algorithms for large classes of problems, in particular for planar graphs and generalizations of planar graphs, and recent lower bound techniques that give evidence that certain types of kernelization algorithms do not exist.

Keywords

fixed parameter tractability kernel kernelization preprocessing data reduction combinatorial problems algorithms 

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© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Hans L. Bodlaender
    • 1
  1. 1.Department of Information and Computing SciencesUtrecht UniversityUtrechtThe Netherlands

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