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A GA-Based Algorithm with a Very Fast Rate of Convergence

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Book cover Computational Intelligence. Theory and Applications (Fuzzy Days 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2206))

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Abstract

In this paper we introduce a new model-free optimization method, which is called as On-line Genetic-Based Algorithm (OGA). In order to compare the performance of the OGA with that of the Conventional Genetic Algorithm (CGA), a constraint optimization problem has been considered. The simulation results show that the OGA remarkably outperform the CGA.

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Author information

Authors and Affiliations

  1. Dept. of Electrical Eng., Amir Kabir University of Tech., Tehran, Iran

    Navid Seifipour & Mohammad B. Menhaj

  2. Dept. of Electrical & Computer Eng., Oklahoma State University, Oklahoma, USA

    Mohammad B. Menhaj

Authors
  1. Navid Seifipour
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  2. Mohammad B. Menhaj
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Editor information

Editors and Affiliations

  1. Computer Science I, University of Dortmund, 44221, Dortmund, Germany

    Bernd Reusch

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© 2001 Springer-Verlag Berlin Heidelberg

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Seifipour, N., Menhaj, M.B. (2001). A GA-Based Algorithm with a Very Fast Rate of Convergence. In: Reusch, B. (eds) Computational Intelligence. Theory and Applications. Fuzzy Days 2001. Lecture Notes in Computer Science, vol 2206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45493-4_23

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  • DOI: https://doi.org/10.1007/3-540-45493-4_23

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42732-2

  • Online ISBN: 978-3-540-45493-9

  • eBook Packages: Springer Book Archive

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