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How Unconventional Chaotic Pseudo-Random Generators Influence Population Diversity in Differential Evolution

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Artificial Intelligence and Soft Computing (ICAISC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10841))

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Abstract

This research focuses on the modern hybridization of the discrete chaotic dynamics and the evolutionary computation. It is aimed at the influence of chaotic sequences on the population diversity as well as at the algorithm performance of the simple parameter adaptive Differential Evolution (DE) strategy: jDE. Experiments are focused on the extensive investigation of totally ten different randomization schemes for the selection of individuals in DE algorithm driven by the default pseudo random generator of Java environment and nine different two-dimensional discrete chaotic systems, as the chaotic pseudo-random number generators. The population diversity and jDE convergence are recorded for 15 test functions from the CEC 2015 benchmark set in 30D.

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Acknowledgements

This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014), further by the European Regional Development Fund under the Project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089 and by Internal Grant Agency of Tomas Bata University. IGA/CebiaTech/2018/003. This work is also based upon support by COST Action CA15140 (ImAppNIO), and COST Action IC406 (cHiPSet). Prof. Zelinka acknowledges following grants/projects: SGS No. 2018/177, VSB-TUO and by the EU’s Horizon 2020 research and innovation programme under grant agreement No. 710577.

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Authors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, 760 01, Zlin, Czech Republic

    Roman Senkerik, Adam Viktorin, Michal Pluhacek & Tomas Kadavy

  2. Faculty of Electrical Engineering and Computer Science, Technical University of Ostrava, 17. listopadu 15, 708 33, Ostrava-Poruba, Czech Republic

    Ivan Zelinka

Authors
  1. Roman Senkerik
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  2. Adam Viktorin
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  3. Michal Pluhacek
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  4. Tomas Kadavy
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  5. Ivan Zelinka
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Corresponding author

Correspondence to Roman Senkerik .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Senkerik, R., Viktorin, A., Pluhacek, M., Kadavy, T., Zelinka, I. (2018). How Unconventional Chaotic Pseudo-Random Generators Influence Population Diversity in Differential Evolution. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2018. Lecture Notes in Computer Science(), vol 10841. Springer, Cham. https://doi.org/10.1007/978-3-319-91253-0_49

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  • DOI: https://doi.org/10.1007/978-3-319-91253-0_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91252-3

  • Online ISBN: 978-3-319-91253-0

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