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Directed Mutation Operators – An Overview

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3683))

Abstract

Directed mutation has shown to improve the efficiency of evolutionary algorithms significantly for a broad spectrum of optimization problems. When the first mutation operators of this kind, however, suffered from the asymmetry parameter influencing the mutation strength, in the meantime there are several new directed mutation operators available which overcome this drawback. The aim of this paper is to give an overview of all different operators in one single place. Their characteristics will be presented and their advantages and disadvantages are discussed. At the end a comparison and a summary is provided.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Dortmund, D-44221, Dortmund, Germany

    Stefan Berlik & Bernd Reusch

Authors
  1. Stefan Berlik
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  2. Bernd Reusch
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Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, BN2 4GJ, Moulsecoomb, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2005 Springer-Verlag Berlin Heidelberg

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Berlik, S., Reusch, B. (2005). Directed Mutation Operators – An Overview. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553939_160

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  • DOI: https://doi.org/10.1007/11553939_160

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28896-1

  • Online ISBN: 978-3-540-31990-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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