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A Uniform-Design Based Multi-objective Adaptive Genetic Algorithm and Its Application to Automated Design of Electronic Circuits

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Advances in Natural Computation (ICNC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4221))

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Abstract

The uniform design technique was integrated into an adaptive genetic algorithm for the sake of optimal design of circuits. The approach proposed features a dynamic evaluation mechanism of multi-objectives, an efficient encoding-decoding scheme based on preferred values, and a classified adaptation strategy of genetic parameters. It was validated by experiments.

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References

  1. Zhao, S.: Study of the evolutionary design methods of electronic circuits. PhD dissertation (in Chinese). Xidian University, Xi’an (2003)

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Author information

Authors and Affiliations

  1. School of Electronic Engineering, Xidian University, Xi’an, 710071, China

    Shuguang Zhao, Xinquan Lai & Mingying Zhao

Authors
  1. Shuguang Zhao
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  2. Xinquan Lai
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  3. Mingying Zhao
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Editor information

Editors and Affiliations

  1. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  3. School of Electronic Engineering, Xidian Univ., 710071, Xi’an, P.R. China

    Xin-bo Gao

  4. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

  5. Multi-Agent Systems Lab,Department of Computer Science, University of Science and Technology of China, 230026, Hefei, China

    Feng Wu

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© 2006 Springer-Verlag Berlin Heidelberg

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Zhao, S., Lai, X., Zhao, M. (2006). A Uniform-Design Based Multi-objective Adaptive Genetic Algorithm and Its Application to Automated Design of Electronic Circuits. In: Jiao, L., Wang, L., Gao, Xb., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881070_89

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  • DOI: https://doi.org/10.1007/11881070_89

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45901-9

  • Online ISBN: 978-3-540-45902-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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