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Ehnanced Grey Wolf Optimizer

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Artificial Intelligence and Soft Computing (ICAISC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14125))

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Abstract

In this paper, we propose EGWO, a new version of Grey Wolf Optimizer. The EGWO algorithm works in almost the same way as the original algorithm, only a simple tool was added into this algorithm. Both algorithms, original and also its new version, are tested on benchmark set of CEC2014 at three levels of dimension, 10, 30, and 50. Our results show that the implementation of our tool makes the Grey Wolf Optimizer significantly more effective in more than 64% of tested problems.

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References

  1. Mirjalili, S., Mirjalili, S.M., Lewis, A.: Grey Wolf optimizer. Adv. Eng. Softw. 69, 46–61 (2014)

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  2. Liang, J.J., Qu, B.Y., Suganthan, P.N.: Problem definitions and evaluation criteria for the CEC 2014 special session and competition on single objective real-parameter numerical optimization. Technical report for single objective optimization competition on CEC 2014 (2013)

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  3. Poláková, R., Tvrdík, J., Bujok, P.: Controlled restart in differential evolution applied to CEC2014 benchmark functions. In: IEEE Congress on Evolutionary Computation 2014, pp. 2230–2236. IEEE, Peking (2014)

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Author information

Authors and Affiliations

  1. Silesian University in Opava, Bezručovo náměstí 1150/13, 746 01, Opava, Czech Republic

    Radka Poláková & Daniel Valenta

Authors
  1. Radka Poláková
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  2. Daniel Valenta
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Corresponding author

Correspondence to Radka Poláková .

Editor information

Editors and Affiliations

  1. Systems Research Institute of the Polish Academy of Sciences, Warsaw, 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 Krakow, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Cite this paper

Poláková, R., Valenta, D. (2023). Ehnanced Grey Wolf Optimizer. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2023. Lecture Notes in Computer Science(), vol 14125. Springer, Cham. https://doi.org/10.1007/978-3-031-42505-9_38

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  • DOI: https://doi.org/10.1007/978-3-031-42505-9_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-42504-2

  • Online ISBN: 978-3-031-42505-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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