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Genetic Algorithm of Tournament Crowding Based on Gaussian Mutation

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Cybernetics and Systems Analysis Aims and scope

Abstract

To solve multimodal optimization problems, a new niching genetic algorithm named tournament crowding genetic algorithm based on Gaussian mutation is proposed. A comparative analysis of this algorithm to other crowding algorithms and to parallel hill-climbing algorithm has shown the advantages of the proposed algorithm in many cases. The FPR criterion to estimate the distribution of population elements is proposed and it is shown that computation of this criterion is advisable to estimate algorithms solving multimodal problems of finding global and local maxima.

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Authors and Affiliations

  1. V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine

    V. P. Shylo

  2. National University of Kyiv-Mohyla Academy, Kyiv, Ukraine

    M. M. Glybovets, N. M. Gulayeva & K. V. Nikishchikhina

Authors
  1. V. P. Shylo
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  2. M. M. Glybovets
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  3. N. M. Gulayeva
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  4. K. V. Nikishchikhina
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Corresponding author

Correspondence to V. P. Shylo.

Additional information

Translated from Kibernetika i Sistemnyi Analiz, No. 2, March–April, 2020, pp. 75–88.

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Shylo, V.P., Glybovets, M.M., Gulayeva, N.M. et al. Genetic Algorithm of Tournament Crowding Based on Gaussian Mutation. Cybern Syst Anal 56, 231–242 (2020). https://doi.org/10.1007/s10559-020-00239-4

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  • DOI: https://doi.org/10.1007/s10559-020-00239-4

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