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Computational Complexity of Evolutionary Algorithms

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Handbook of Natural Computing

Abstract

When applying evolutionary algorithms to the task of optimization it is important to have a clear understanding of their capabilities and limitations. By analyzing the optimization time of various variants of evolutionary algorithms for classes of concrete optimization problems, important insights can be gained about what makes problems easy or hard for these heuristics. Still more important than the derivation of such specific results is the development of methods that facilitate rigorous analysis and enable researchers to derive such results for new variants of evolutionary algorithms and more complex problems. The development of such methods and analytical tools is a significant and very active area of research. An overview of important methods and their foundations is presented together with exemplary applications. This enables one to apply these methods to concrete problems and participate in the theoretical foundation of evolutionary computing.

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Acknowledgment

This material is based upon works supported by Science Foundation Ireland under Grant No. 07/SK/I1205.

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Authors and Affiliations

  1. Department of Computer Science, University College Cork, Cork, Ireland

    Thomas Jansen

Authors
  1. Thomas Jansen
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Editor information

Editors and Affiliations

  1. LIACS, Leiden University, Leiden, The Netherlands

    Grzegorz Rozenberg

  2. Computer Science Department, University of Colorado, Boulder, USA

    Grzegorz Rozenberg

  3. LIACS, Leiden University, Leiden, The Netherlands

    Thomas Bäck

  4. LIACS, Leiden University, Leiden, The Netherlands

    Joost N. Kok

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© 2012 Springer-Verlag Berlin Heidelberg

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Jansen, T. (2012). Computational Complexity of Evolutionary Algorithms. In: Rozenberg, G., Bäck, T., Kok, J.N. (eds) Handbook of Natural Computing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92910-9_26

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