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A Bio Inspired Estimation of Distribution Algorithm for Global Optimization

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Neural Information Processing (ICONIP 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7665))

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Abstract

This paper introduces a new bio-inspired Estimation of Distribution Algorithm for global optimization that integrates the quantum computing concepts with the immune clonal selection, vaccination process and Estimation of Distribution Algorithm (EDA). EDA is employed in the vaccination process to improve the solutions diversity and maintain high quality solutions in addition to its ability to avoid falling in local optimum for multi modal problems. The proposed algorithm is implemented and evaluated using standard benchmark test problems. Experimental results are compared with the quantum inspired immune clonal algorithm (QICA) and the QICA- with vaccine algorithm, where the proposed algorithm is superior to both of them. The obtained results carried out, it is performing well in terms of the solutions quality and diversity, and it is superior to both of compared algorithms.

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Author information

Authors and Affiliations

  1. Faculty of Computers and Information, Cairo University, 5 Ahmed Zewal Street, Orman, Giza, Egypt

    Omar S. Soliman & Aliaa Rassem

Authors
  1. Omar S. Soliman
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  2. Aliaa Rassem
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Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Education City, P.O. Box 23874, Doha, Qatar

    Tingwen Huang

  2. Department of Control Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, 430074, Wuhan, Hubei, China

    Zhigang Zeng

  3. College of Computer Science, Chongqing University, 174 Shazhengjie Street, 400044, Chongqing, China

    Chuandong Li

  4. Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

    Chi Sing Leung

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© 2012 Springer-Verlag Berlin Heidelberg

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Soliman, O.S., Rassem, A. (2012). A Bio Inspired Estimation of Distribution Algorithm for Global Optimization. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7665. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34487-9_78

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  • DOI: https://doi.org/10.1007/978-3-642-34487-9_78

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34486-2

  • Online ISBN: 978-3-642-34487-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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