A1 Journal article (refereed)
Impact of chaotic dynamics on the performance of metaheuristic optimization algorithms : An experimental analysis (2022)
Zelinka, I., Diep, Q. B., Snášel, V., Das, S., Innocenti, G., Tesi, A., Schoen, F., & Kuznetsov, N. V. (2022). Impact of chaotic dynamics on the performance of metaheuristic optimization algorithms : An experimental analysis. Information Sciences, 587, 692-719. https://doi.org/10.1016/j.ins.2021.10.076
JYU authors or editors
Publication details
All authors or editors: Zelinka, Ivan; Diep, Quoc Bao; Snášel, Václav; Das, Swagatam; Innocenti, Giacomo; Tesi, Alberto; Schoen, Fabio; Kuznetsov, Nikolai V.
Journal or series: Information Sciences
ISSN: 0020-0255
eISSN: 1872-6291
Publication year: 2022
Volume: 587
Pages range: 692-719
Publisher: Elsevier
Publication country: Netherlands
Publication language: English
DOI: https://doi.org/10.1016/j.ins.2021.10.076
Publication open access: Openly available
Publication channel open access: Partially open access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/79478
Abstract
Random mechanisms including mutations are an internal part of evolutionary algorithms, which are based on the fundamental ideas of Darwin’s theory of evolution as well as Mendel’s theory of genetic heritage. In this paper, we debate whether pseudo-random processes are needed for evolutionary algorithms or whether deterministic chaos, which is not a random process, can be suitably used instead. Specifically, we compare the performance of 10 evolutionary algorithms driven by chaotic dynamics and pseudo-random number generators using chaotic processes as a comparative study. In this study, the logistic equation is employed for generating periodical sequences of different lengths, which are used in evolutionary algorithms instead of randomness. We suggest that, instead of pseudo-random number generators, a specific class of deterministic processes (based on deterministic chaos) can be used to improve the performance of evolutionary algorithms. Finally, based on our findings, we propose new research questions.
Keywords: chaos theory; evolutionary computation; swarm intelligence; algorithms; algorithmics
Free keywords: deterministic chaos; swarm intelligence; evolutionary algorithms; algorithm dynamics; algorithm performance
Contributing organizations
Ministry reporting: Yes
VIRTA submission year: 2022
JUFO rating: 2