New Races in Parameterized Algorithmics

  • Christian Komusiewicz
  • Rolf Niedermeier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7464)


Once having classified an NP-hard problem fixed-parameter tractable with respect to a certain parameter, the race for the most efficient fixed-parameter algorithm starts. Herein, the attention usually focuses on improving the running time factor exponential in the considered parameter, and, in case of kernelization algorithms, to improve the bound on the kernel size. Both from a practical as well as a theoretical point of view, however, there are further aspects of efficiency that deserve attention. We discuss several of these aspects and particularly focus on the search for “stronger parameterizations” in developing fixed-parameter algorithms.


Vertex Cover Input Graph Outerplanar Graph Solution Size Problem Kernel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Christian Komusiewicz
    • 1
  • Rolf Niedermeier
    • 1
  1. 1.Institut für Softwaretechnik und Theoretische InformatikTU BerlinGermany

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