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Evolutionary Algorithms for Chaos Researchers

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Evolutionary Algorithms and Chaotic Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 267))

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Abstract

Evolutionary algorithms are search methods that can be used for solving optimization problems. They mimic working principles from natural evolution by employing a population—based approach, labeling each individual of the population with a fitness and including elements of random, albeit the random is directed through a selection process. In this chapter, we review the basic principles of evolutionary algorithms and discuss their purpose, structure and behavior. In doing so, it is particularly shown how the fundamental understanding of natural evolution processes has cleared the ground for the origin of evolutionary algorithms. Major implementation variants and their structural as well as functional elements are discussed. We also give a brief overview on usability areas of the algorithm and end with some general remarks of the limits of computing.

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Author information

Authors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, Zlin, 76001, Czech Republic

    Ivan Zelinka

  2. Faculty of Electrical Engineering and Computer Science, VSB-TUO, 17. listopadu 15, 708 33, Ostrava-Poruba, Czech Republic

    Ivan Zelinka

  3. Fakultät Elektrotechnik und Informationstechnik, HTWK Leipzig, D-04251, Leipzig, Germany

    Hendrik Richter

Authors
  1. Ivan Zelinka
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  2. Hendrik Richter
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Editor information

Editors and Affiliations

  1. Department of Applied Informatics Faculty of Applied Informatics, Tomas Bata Univerzity in Zlin, Nad Stranemi 4511, Zlin, 76001, Czech Republic

    Ivan Zelinka

  2. Department of Control Engineering Faculty of Electrical Engineering, Czech Technical University in Prague UTIA AV CR, Pod vodarenskou vezi 4, 182 08, Prague 8, Czech Republic

    Sergej Celikovsky

  3. Faculty of Electrical Engineering & Information Technology, HTWK Leipzig, 04251, Leipzig, Germany

    Hendrik Richter

  4. Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR P. R. China

    Guanrong Chen

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Zelinka, I., Richter, H. (2010). Evolutionary Algorithms for Chaos Researchers. In: Zelinka, I., Celikovsky, S., Richter, H., Chen, G. (eds) Evolutionary Algorithms and Chaotic Systems. Studies in Computational Intelligence, vol 267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10707-8_2

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  • DOI: https://doi.org/10.1007/978-3-642-10707-8_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10706-1

  • Online ISBN: 978-3-642-10707-8

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