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Multi-Population Genetic Programming with Data Migration for Symbolic Regression

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Computational Intelligence and Efficiency in Engineering Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 595))

Abstract

In this contribution we study the effects of multi-population genetic programming for symbolic regression problems. In addition to the parallel evolution of several subpopulations according to an island model with unidirectional ring migration, the data partitions, on which the individuals are evolved, differ for every island and are adapted during algorithm execution. These modifications are intended to increase the generalization capabilities of the solutions and to maintain the genetic diversity. The effects of multiple populations as well as the used data migration strategy are compared to standard genetic programming algorithms on several symbolic regression benchmark problems.

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  1. 1.

    http://dev.heuristiclab.com.

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Authors and Affiliations

  1. School of Informatics, Communications and Media, University of Applied Sciences Upper Austria, Softwarepark 11, 4232, Hagenberg, Austria

    Michael Kommenda, Michael Affenzeller, Gabriel Kronberger, Bogdan Burlacu & Stephan Winkler

  2. Institute for Formal Models and Verification, Johannes Kepler University Linz, Altenbergerstr. 69, 4040, Linz, Austria

    Michael Kommenda, Michael Affenzeller & Bogdan Burlacu

Authors
  1. Michael Kommenda
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  2. Michael Affenzeller
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  3. Gabriel Kronberger
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  4. Bogdan Burlacu
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  5. Stephan Winkler
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Corresponding author

Correspondence to Michael Kommenda .

Editor information

Editors and Affiliations

  1. Warsaw University of Technology, Warsaw, Poland

    Grzegorz Borowik

  2. University of Technology, Sydney, New South Wales, Australia

    Zenon Chaczko

  3. University of Applied Sciences Upper Austria, Hagenberg, Austria

    Witold Jacak

  4. Warsaw University of Technology, Warsaw, Poland

    Tadeusz Łuba

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Kommenda, M., Affenzeller, M., Kronberger, G., Burlacu, B., Winkler, S. (2015). Multi-Population Genetic Programming with Data Migration for Symbolic Regression. In: Borowik, G., Chaczko, Z., Jacak, W., Łuba, T. (eds) Computational Intelligence and Efficiency in Engineering Systems. Studies in Computational Intelligence, vol 595. Springer, Cham. https://doi.org/10.1007/978-3-319-15720-7_6

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  • DOI: https://doi.org/10.1007/978-3-319-15720-7_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15719-1

  • Online ISBN: 978-3-319-15720-7

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