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Self-Adaptive Chaos Differential Evolution

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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

Differential evolution (DE) is a recently invented global optimization algorithm. In this paper, a new differential evolution algorithm, self-adaptive chaos differential evolution (SACDE) with chaos mutation factor and dynamically changing weighting factor and crossover factor is presented. The evolution speed factor and aggregation degree factor of the population are introduced in this new algorithm. In each iteration process, the weighting factor is changed dynamically based on the current aggregation degree factor, and the crossover factor is changed dynamically based on the current evolution speed factor. The chaos mutation factor is introduced to avoid falling into the local optimum. DE and SACDE are tested with two well-known benchmark functions. The experiments show that the convergence speed of SACDE is significantly superior to DE, the convergence accuracy is also increased.

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References

  1. DE Homepage: http://www.icsi.berkeley.edu/~storn/code.html

  2. Xuanping, Z., Yuping, D.: Adaptive Particle Swarm Algorithm with Dynamically Changing Intertia Weight. Journal of Xi’an Jiaotong University 39(10), 1039–1042 (2005)

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Author information

Authors and Affiliations

  1. Research & Development Center of Electric Vehicle, Xi’an Jiaotong University, Xi’an, 710049, China

    Guo Zhenyu, Cheng Bo, Ye Min & Cao Binggang

Authors
  1. Guo Zhenyu
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  2. Cheng Bo
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  3. Ye Min
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  4. Cao Binggang
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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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Zhenyu, G., Bo, C., Min, Y., Binggang, C. (2006). Self-Adaptive Chaos Differential Evolution. 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_128

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  • DOI: https://doi.org/10.1007/11881070_128

  • 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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