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European Conference on Genetic Programming

EuroGP 2009: Genetic Programming pp 85–96Cite as

The Role of Population Size in Rate of Evolution in Genetic Programming

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5481))

Abstract

Population size is a critical parameter that affects the performance of an Evolutionary Computation model. A variable population size scheme is considered potentially beneficial to improve the quality of solutions and to accelerate fitness progression. In this contribution, we discuss the relationship between population size and the rate of evolution in Genetic Programming. We distinguish between the rate of fitness progression and the rate of genetic substitutions, which capture two different aspects of a GP evolutionary process. We suggest a new indicator for population size adjustment during an evolutionary process by measuring the rate of genetic substitutions. This provides a separate feedback channel for evolutionary process control, derived from concepts of population genetics. We observe that such a strategy can stabilize the rate of genetic substitutions and effectively accelerate fitness progression. A test with the Mackey-Glass time series prediction verifies our observations.

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Authors and Affiliations

  1. Department of Computer Science, Memorial University, St. John’s, Canada

    Ting Hu & Wolfgang Banzhaf

Authors
  1. Ting Hu
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  2. Wolfgang Banzhaf
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Editor information

Editors and Affiliations

  1. Department of Informatics, Systems and Communication (D.I.S.Co.), University of Milano-Bicocca, viale Sarca 336-U14, 20126, Milano, Italy

    Leonardo Vanneschi

  2. GE Global Research, NY 12309, Niskayuna, USA

    Steven Gustafson

  3. Department of Computer Engineering, University of Coimbra, Polo II - Pinhal de Marrocos, 3030, Coimbra, Portugal

    Alberto Moraglio

  4. Institute of High Performance Computing and Networking, National Research Council of Italy (ICAR - CNR), Via P. Castellino 111, 80131, Napoli, Italy

    Ivanoe De Falco

  5. Wilhelm Schickard Institut für Informatik, Eberhard Karls Universität Tübingen, Abt. Rechnerarchitektur, Sand 1, 72076, Tübingen, Germany

    Marc Ebner

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Hu, T., Banzhaf, W. (2009). The Role of Population Size in Rate of Evolution in Genetic Programming. In: Vanneschi, L., Gustafson, S., Moraglio, A., De Falco, I., Ebner, M. (eds) Genetic Programming. EuroGP 2009. Lecture Notes in Computer Science, vol 5481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01181-8_8

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  • DOI: https://doi.org/10.1007/978-3-642-01181-8_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01180-1

  • Online ISBN: 978-3-642-01181-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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