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Generalized Evolutionary Algorithms

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Handbook of Natural Computing

Abstract

People have been inventing and tinkering with various forms of evolutionary algorithms (EAs) since the 1950s when digital computers became more readily available to scientists and engineers. Today we see a wide variety of EAs and an impressive array of applications. This diversity is both a blessing and a curse. It serves as strong evidence for the usefulness of these techniques, but makes it difficult to see “the big picture” and make decisions regarding which EAs are best suited for new application areas. The purpose of this chapter is to provide a broader “generalized” perspective.

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Author information

Authors and Affiliations

  1. Department of Computer Science, George Mason University, Fairfax, VA, USA

    Kenneth De Jong

Authors
  1. Kenneth De Jong
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Corresponding author

Correspondence to Kenneth De Jong .

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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De Jong, K. (2012). Generalized 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_20

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