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Experimenting with a New Population-Based Optimization Technique: FUNgal Growth Inspired (FUNGI) Optimizer

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Recent Developments and the New Direction in Soft-Computing Foundations and Applications

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 361))

Abstract

In this paper the experimental results of a new evolutionary algorithm are presented. The proposed method was inspired by the growth and reproduction of fungi. Experiments were executed and evaluated on discretized versions of common functions, which are used in benchmark tests of optimization techniques. The results were compared with other optimization algorithms and the directions of future research with many possible modifications/extension of the presented method are discussed.

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Acknowledgements

This paper was partially supported by the National Research, Development and Innovation Office (NKFIH) K105529, K108405. The implementations of the used benchmark functions are based on the work of J. D. McCaffrey [21], S. Surjanovic and D. Bingham [22].

Author information

Authors and Affiliations

  1. Department of Information Technology, Széchenyi István University, Győr, Hungary

    A. Tormási & L. T. Kóczy

  2. Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Budapest, Hungary

    L. T. Kóczy

Authors
  1. A. Tormási
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  2. L. T. Kóczy
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Corresponding author

Correspondence to A. Tormási .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  2. Machine Intelligence Institute, Iona College, New Rochelle, New York, USA

    Ronald R. Yager

  3. Department of Information Technology and Programming, Azerbaijan Technical University, Baku, Azerbaijan

    Shahnaz N. Shahbazova

  4. Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Marek Z. Reformat

  5. Department of Computer Science, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

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Tormási, A., Kóczy, L.T. (2018). Experimenting with a New Population-Based Optimization Technique: FUNgal Growth Inspired (FUNGI) Optimizer. In: Zadeh, L., Yager, R., Shahbazova, S., Reformat, M., Kreinovich, V. (eds) Recent Developments and the New Direction in Soft-Computing Foundations and Applications. Studies in Fuzziness and Soft Computing, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-319-75408-6_11

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  • DOI: https://doi.org/10.1007/978-3-319-75408-6_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75407-9

  • Online ISBN: 978-3-319-75408-6

  • eBook Packages: EngineeringEngineering (R0)

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