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Multiobjective Problem Solving from Nature pp 177–200Cite as

Reducing Bloat in GP with Multiple Objectives

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Part of the book series: Natural Computing Series ((NCS))

Summary

This chapter investigates the use of multiobjective techniques in genetic programming (GP) in order to evolve compact programs and to reduce the effects caused by bloating. The underlying approach considers the program size as a second, independent objective besides program functionality, and several studies have found this concept to be successful in reducing bloat. Based on one specific algorithm, we demonstrate the principle of multiobjective GP and show how to apply Pareto-based strategies to GP. This approach outperforms four classical strategies to reduce bloat with regard to both convergence speed and size of the produced programs on an even-parity problem. Additionally, we investigate the question of why the Pareto-based strategies can be more effective in reducing bloat than alternative strategies on several test problems. The analysis falsifies the hypothesis that the small but less functional individuals that are kept in the population act as building blocks building blocks for larger correct solutions. This leads to the conclusion that the advantages are probably due to the increased diversity in the population.

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Author information

Authors and Affiliations

  1. Computer Engineering and Networks Laboratory (TIK), ETH Zurich, Switzerland

    Stefan Bleuler, Johannes Bader & Eckart Zitzler

Authors
  1. Stefan Bleuler
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  2. Johannes Bader
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  3. Eckart Zitzler
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Editor information

Editors and Affiliations

  1. Manchester Interdisciplinary Biocentre, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK

    Joshua Knowles

  2. Room G39 Earl Mountbatten Building, Heriot-Watt University, Edinburgh EH14 4AS, UK

    David Corne

  3. Dept. of Business Technology, Helsinki School of Economics, P.O. Box 1210, FIN-00101 Helsinki, Finland

    Kalyanmoy Deb (Deva Raj Chair Professor) (Deva Raj Chair Professor)

  4. Dept. of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur,Pin 208016, India

    Kalyanmoy Deb (Deva Raj Chair Professor) (Deva Raj Chair Professor)

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© 2008 Springer-Verlag Berlin Heidelberg

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Bleuler, S., Bader, J., Zitzler, E. (2008). Reducing Bloat in GP with Multiple Objectives. In: Knowles, J., Corne, D., Deb, K. (eds) Multiobjective Problem Solving from Nature. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72964-8_9

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  • DOI: https://doi.org/10.1007/978-3-540-72964-8_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72963-1

  • Online ISBN: 978-3-540-72964-8

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