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A Dynamic Convexized Function with the Same Global Minimizers for Global Optimization

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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

We consider the box constrained continuous global minimization problem. We present an auxiliary function T(x, k, p), which has the same global minimizers as the problem if p is large enough. The minimization of T(x, k, p) can escape successfully from a previously converged local minimizer by taking the value of k increasingly. We propose an algorithm to find a global minimizer of the box constrained continuous global minimization problem by minimizing T(x, k, p) dynamically. Numerical experiments on two sets of standard testing problems show that the algorithm is effective, and is competent with some well known global minimization methods.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Fuzhou University, Fuzhou, 350002, China

    Wenxing Zhu

Authors
  1. Wenxing Zhu
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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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Zhu, W. (2006). A Dynamic Convexized Function with the Same Global Minimizers for Global Optimization. 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_124

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  • DOI: https://doi.org/10.1007/11881070_124

  • 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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