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Kernelization: New Upper and Lower Bound Techniques

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Parameterized and Exact Computation (IWPEC 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5917))

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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.

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  1. Department of Information and Computing Sciences, Utrecht University, P.O. Box 80.089, 3508, TB, Utrecht, The Netherlands

    Hans L. Bodlaender

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  1. Hans L. Bodlaender
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  1. Department of Computer Science and Engineering, Texas A&M University, College Station, 77843, Texas, USA

    Jianer Chen

  2. Institutt for informatikk, Universitetet i Bergen, Postboks 7803, 5020, Bergen, Norway

    Fedor V. Fomin

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Bodlaender, H.L. (2009). Kernelization: New Upper and Lower Bound Techniques. In: Chen, J., Fomin, F.V. (eds) Parameterized and Exact Computation. IWPEC 2009. Lecture Notes in Computer Science, vol 5917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11269-0_2

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