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Quantum-Inspired Evolutionary Algorithms and Its Application to Numerical Optimization Problems

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Book cover Neural Information Processing (ICONIP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3316))

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Abstract

This work proposes a new kind of evolutionary algorithm inspired in the principles of quantum computing. This algorithm is an extension of a proposed model for combinatorial optimization problems which uses a binary representation for the chromosome. This extension uses probability distributions for each free variable of the problem, in order to simulate the superposition of solutions, which is intrinsic in the quantum computing methodology. A set of mathematical operations is used as implicit genetic operators over those probability distributions. The efficiency and the applicability of the algorithm are demonstrated through experimental results using the F6 function.

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References

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Author information

Authors and Affiliations

  1. ICA – Applied Computational Intelligence Lab, Electrical Engineering Department, Pontifícia Universidade Católica do, Rio de Janeiro

    André V. Abs da Cruz, Carlos R. Hall Barbosa, Marco Aurélio C. Pacheco & Marley Vellasco

  2. Department of Computer Science, University College of London, UK

    Marley Vellasco

Authors
  1. André V. Abs da Cruz
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  2. Carlos R. Hall Barbosa
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  3. Marco Aurélio C. Pacheco
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  4. Marley Vellasco
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Editor information

Editors and Affiliations

  1. Indian Statistical Institute, Electronics and Communication Sciences Unit, Kolkata, India

    Nikhil Ranjan Pal

  2. School of Computer and Information Sciences, Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland University of Technology, Private Bag 92006, Auckland, New Zealand

    Nik Kasabov

  3. Department of Instrumentation and Electronics Engineering, Jadavpur University, Salt-lake Campus, 700098, Calcutta, India

    Rajani K. Mudi

  4. Indian Statistical Institute, 203 B. T. Road, 700 108, Calcutta,  

    Srimanta Pal

  5. Indian Statistical Institute, Computer Vision and Pattern Recognition Unit, 700108, Kolkata, India

    Swapan Kumar Parui

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© 2004 Springer-Verlag Berlin Heidelberg

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Abs da Cruz, A.V., Hall Barbosa, C.R., Pacheco, M.A.C., Vellasco, M. (2004). Quantum-Inspired Evolutionary Algorithms and Its Application to Numerical Optimization Problems. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_31

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  • DOI: https://doi.org/10.1007/978-3-540-30499-9_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23931-4

  • Online ISBN: 978-3-540-30499-9

  • eBook Packages: Springer Book Archive

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