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Evolutionary Algorithm Parameters and Methods to Tune Them

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Autonomous Search

Abstract

In this chapter we discuss the notion of Evolutionary Algorithm (EAs) parameters and propose a distinction between EAs and EA instances, based on the type of parameters used to specify their details. Furthermore, we consider the most important aspects of the parameter tuning problem and give an overview of existing parameter tuning methods. Finally, we elaborate on the methodological issues involved here and provide recommendations for further development.

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Author information

Authors and Affiliations

  1. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    A. E. Eiben

Authors
  1. A. E. Eiben
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  2. S. K. Smit
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Corresponding author

Correspondence to A. E. Eiben .

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Editors and Affiliations

  1. Microsoft Research Cambridge, JJ Thomson Avenue 7, Cambridge, CB3 0FB, United Kingdom

    Youssef Hamadi

  2. Federico Santa María, Departamento de Informática, Universidad Técnica, Avenida España 1680, Valparaíso, Chile

    Eric Monfroy

  3. Faculté des Sciences, LERIA, Université d'Angers, Boulevard Lavoisier 2, Angers CX 01, 49045, France

    Frédéric Saubion

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Eiben, A.E., Smit, S.K. (2011). Evolutionary Algorithm Parameters and Methods to Tune Them. In: Hamadi, Y., Monfroy, E., Saubion, F. (eds) Autonomous Search. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21434-9_2

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  • DOI: https://doi.org/10.1007/978-3-642-21434-9_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21433-2

  • Online ISBN: 978-3-642-21434-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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