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Iterative Compression for Exactly Solving NP-Hard Minimization Problems

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Algorithmics of Large and Complex Networks

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5515))

Abstract

We survey the conceptual framework and several applications of the iterative compression technique introduced in 2004 by Reed, Smith, and Vetta. This technique has proven very useful for achieving a number of recent breakthroughs in the development of fixed-parameter algorithms for NP-hard minimization problems. There is a clear potential for further applications as well as a further development of the technique itself. We describe several algorithmic results based on iterative compression and point out some challenges for future research.

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Authors and Affiliations

  1. Institut für Informatik, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, D-07743, Jena, Germany

    Jiong Guo, Hannes Moser & Rolf Niedermeier

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  1. Jiong Guo
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  2. Hannes Moser
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  3. Rolf Niedermeier
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Editor information

Editors and Affiliations

  1. Department of Computer & Information Science, University of Konstanz, 78457, Konstanz, Germany

    Jürgen Lerner

  2. Institute of Theoretical Informatics, Technical University of Karlsruhe, 76128, Karlsruhe, Germany

    Dorothea Wagner

  3. Department of Biological Physics, Eötvös Lorand University, Pazmany P. Stny 1A, 1117, Budapest, Hungary

    Katharina A. Zweig

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Guo, J., Moser, H., Niedermeier, R. (2009). Iterative Compression for Exactly Solving NP-Hard Minimization Problems. In: Lerner, J., Wagner, D., Zweig, K.A. (eds) Algorithmics of Large and Complex Networks. Lecture Notes in Computer Science, vol 5515. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02094-0_4

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  • DOI: https://doi.org/10.1007/978-3-642-02094-0_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02093-3

  • Online ISBN: 978-3-642-02094-0

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