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Unified Chromosome Representation for Large Scale Problems

  • Conference paper
Multiple Approaches to Intelligent Systems (IEA/AIE 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1611))

  • 930 Accesses

Abstract

Genetic Algorithms have been successfully applied to the function optimization problem. However, the main disadvantage of this technique is its large chromosome length and hence long conversion time specially when applied to functions with a large number of parameters. In this paper, a new chromosome representation scheme that reduces the chromosome length is proposed. The scheme is also domain independent and may be used with any function. Results and a comparison between the conventional chromosome representation and the proposed one are presented.

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Cairo University,  

    Hoda A. Baraka, Saad Eid & Hanan Kamal

  2. Computers and Systems Dept., Electronics Research Institute, Dokki, Giza

    Ashraf H. Abdel Wahab

Authors
  1. Hoda A. Baraka
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  2. Saad Eid
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  3. Hanan Kamal
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  4. Ashraf H. Abdel Wahab
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Editor information

Editors and Affiliations

  1. Thinking Machines Corporation, 16 New England Executive Park, 01803, Burlington, MA, USA

    Ibrahim Imam

  2. LRI, UMR CNRS 8623, Bât, 490, Université de Paris-Sud 11, 91405, Orsay, France

    Yves Kodratoff

  3.  ,  

    Ayman El-Dessouki

  4. Department of Computer Science, Texas State University-San Marcos, Nueces 247, 601 University Drive, 78666-4616, San Marcos, TX, USA

    Moonis Ali

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© 1999 Springer-Verlag Berlin Heidelberg

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Baraka, H.A., Eid, S., Kamal, H., Abdel Wahab, A.H. (1999). Unified Chromosome Representation for Large Scale Problems. In: Imam, I., Kodratoff, Y., El-Dessouki, A., Ali, M. (eds) Multiple Approaches to Intelligent Systems. IEA/AIE 1999. Lecture Notes in Computer Science(), vol 1611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48765-4_80

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  • DOI: https://doi.org/10.1007/978-3-540-48765-4_80

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66076-7

  • Online ISBN: 978-3-540-48765-4

  • eBook Packages: Springer Book Archive

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