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An Adaptive Penalty Scheme for Steady-State Genetic Algorithms

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Genetic and Evolutionary Computation — GECCO 2003 (GECCO 2003)

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Abstract

A parameter-less adaptive penalty scheme for steady-state genetic algorithms applied to constrained optimization problems is proposed. For each constraint, a penalty parameter is adaptively computed along the run according to information extracted from the current population such as the existence of feasible individuals and the level of violation of each constraint. Using real coding, rank-based selection, and operators available in the literature, very good results are obtained.

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Author information

Authors and Affiliations

  1. LNCC/MCT, Rua Getulio Vargas 333, 25651 070, Petropolis RJ, Brazil

    Helio J. C. Barbosa

  2. Depto. de Estruturas, Faculdade de Engenharia, Universidade Federal de Juiz de Fora, 36036 330, Juiz de Fora MG, Brazil

    Afonso C. C. Lemonge

Authors
  1. Helio J. C. Barbosa
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  2. Afonso C. C. Lemonge
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Editor information

Editors and Affiliations

  1. Lawrence Livermore National Laboratory, Center for Applied Scientific Computing (CASC), 7000 East Avenue, L-561, Livermore, CA, 94550, USA

    Erick Cantú-Paz

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© 2003 Springer-Verlag Berlin Heidelberg

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Barbosa, H.J.C., Lemonge, A.C.C. (2003). An Adaptive Penalty Scheme for Steady-State Genetic Algorithms. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45105-6_87

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  • DOI: https://doi.org/10.1007/3-540-45105-6_87

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40602-0

  • Online ISBN: 978-3-540-45105-1

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