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Dynamic Control of Adaptive Parameters in Evolutionary Programming

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Book cover Simulated Evolution and Learning (SEAL 1998)

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Abstract

Evolutionary programming (EP) has been widely used in numerical optimization in recent years. The adaptive parameters, also named step size control, in EP play a significant role which controls the step size of the objective variables in the evolutionary process. However, the step size control may not work in some cases. They are frequently lost and then make the search stagnate early. Applying the lower bound can maintain the step size in a work range, but it also constrains the objective variables from being further explored. In this paper, an adaptively adjusted lower bound is proposed which supports better fine-tune searches and spreads out exploration as well.

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Author information

Authors and Affiliations

  1. Computational Intelligence Group, School of Computer Science University College, The University of New South Wales Australian Defence Force Academy, Canberra, ACT, 2600, Australia

    Ko-Hsin Liang, Xin Yao & Charles Newton

Authors
  1. Ko-Hsin Liang
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  2. Xin Yao
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  3. Charles Newton
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Editor information

Editors and Affiliations

  1. School of Computer Science, University College, UNSW Australian Defence Force Academy, Canberra, ACT, Australia, 2600

    Bob McKay , Xin Yao  & Charles S. Newton ,  & 

  2. Department of Electrical Engineering Korea Advanced Institute of Science and Technology, 373-1, Kusung-dong, Yusung-gu, Taejon-shi, 305-701, Korea

    Jong-Hwan Kim

  3. Department of Information Electronics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8603, Japan

    Takeshi Furuhashi

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© 1999 Springer-Verlag Berlin Heidelberg

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Liang, KH., Yao, X., Newton, C. (1999). Dynamic Control of Adaptive Parameters in Evolutionary Programming. In: McKay, B., Yao, X., Newton, C.S., Kim, JH., Furuhashi, T. (eds) Simulated Evolution and Learning. SEAL 1998. Lecture Notes in Computer Science(), vol 1585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48873-1_7

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  • DOI: https://doi.org/10.1007/3-540-48873-1_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65907-5

  • Online ISBN: 978-3-540-48873-6

  • eBook Packages: Springer Book Archive

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