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Asia-Pacific Conference on Simulated Evolution and Learning

SEAL 2006: Simulated Evolution and Learning pp 277–283Cite as

An Accelerated Micro Genetic Algorithm for Numerical Optimization

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4247))

Abstract

In this paper, we present an accelerated micro genetic algorithm for numerical optimization. It is implemented by incorporating the conventional micro genetic algorithm with a local optimizer based on heuristic pattern move and Aitken Δ2 acceleration method. Performance tests with three benchmarking functions indicate that the presented algorithm has excellent convergence performance for multimodal optimization problems. The number of objective function evaluations required to obtain global optima is only 5.4-11.9% of that required by using conventional micro genetic algorithm.

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References

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Author information

Authors and Affiliations

  1. College of Hydraulic Science & Engineering, Yangzhou University, Yangzhou, 225009, PR China

    Linsong Sun & Weihua Zhang

Authors
  1. Linsong Sun
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  2. Weihua Zhang
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Editor information

Editors and Affiliations

  1. Department of Industrial Engineering and Management, Cheng Shiu University, Kaohsiung County Taiwan, ROC

    Tzai-Der Wang

  2. School of Computer Science and information Technology, RMIT University, VIC 3001, Melbourne, Australia

    Xiaodong Li

  3. AI-ECON Research Center, Department of Economics, National Chengchi University, 11623, Taipei, Taiwan

    Shu-Heng Chen

  4. Department of Computer Science and Technology, University of Sci. & Tech. of China, 230026, Hefei, Anhui, P.R. China

    Xufa Wang

  5. School of Information Technology and Electrical Engineering, University of New South Wales, Australian Defence Force Academy, Canberra, Australia

    Hussein Abbass

  6. The Univertity of Tokyo, Japan

    Hitoshi Iba

  7. Department of Computer, University of Science and Technology of China, 230027, Hefei, China

    Guo-Liang Chen

  8. University of Birmingham, Birmingham, UK

    Xin Yao

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Sun, L., Zhang, W. (2006). An Accelerated Micro Genetic Algorithm for Numerical Optimization. In: Wang, TD., et al. Simulated Evolution and Learning. SEAL 2006. Lecture Notes in Computer Science, vol 4247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11903697_36

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  • DOI: https://doi.org/10.1007/11903697_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-47331-2

  • Online ISBN: 978-3-540-47332-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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