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Evolutionary Elementary Cooperative Strategy for Global Optimization

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4253))

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Abstract

Nonlinear functions optimization is still a challenging problem of great importance. This paper proposes a novel optimization technique called Evolutionary Elementary Cooperative Strategy (EECS) that integrates ideas form interval division in an evolutionary scheme. We compare the performances of the proposed algorithm with the performances of three well established global optimization techniques namely Interval Branch and Bound with Local Sampling (IVL), Advanced Scatter Search (ASS) and Simplex Coding Genetic Algorithm (SCGA). We also present the results obtained by EECS for higher dimension functions. Empirical results for the functions considered reveal that the proposed method is promising.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Babeş-Bolyai University, Cluj-Napoca, 3400, Romania

    Crina Grosan

  2. School of Computer Science and Engineering Chung-Ang University, Seoul, 156-756, Korea

    Ajith Abraham & Tae-Gyu Chang

  3. Avram Iancu University, Cluj-Napoca, 3400, Romania

    Monica Chis

Authors
  1. Crina Grosan
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  2. Ajith Abraham
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  3. Monica Chis
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  4. Tae-Gyu Chang
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Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK

    Bogdan Gabrys

  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, 5095, SA, Australia

    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Grosan, C., Abraham, A., Chis, M., Chang, TG. (2006). Evolutionary Elementary Cooperative Strategy for Global Optimization. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893011_86

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  • DOI: https://doi.org/10.1007/11893011_86

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46542-3

  • Online ISBN: 978-3-540-46544-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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