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Limited Randomness Evolutionary Strategy Algorithm

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Mendel 2015 (ICSC-MENDEL 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 378))

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Abstract

Herein presented paper is denoted to study of real requirements of evolutionary algorithm to random number generator properties. In the past years novel studies occurred. These studies pointed that in some situations random number generator might be replaced by deterministic chaos system. The goal of presented paper is to point the significant properties of number generator, to extend the class of systems to use on its place. During preparation of the paper experiments with Evolutionary Strategy algorithm were done and as the test- bed problems of identification of parameters of two deterministic chaos systems were used. Namely, these systems were Lorenz and Rabinovich-Fabricant ones. The conclusion of the paper is, that periodic functions might be used if proper parameters and sampling period of number generating function replacing random number generator are chosen. This result is not so interesting from practical viewpoint, because the application of sin(x) function is slower than standard rand() function of C and C++ language, but it points that evolutionary algorithms do not require randomness as the source of its capabilities.

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Authors and Affiliations

  1. Faculty of Transportation Sciences, CTU in Prague, Prague, Czech Republic

    Tomas Brandejsky

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  1. Tomas Brandejsky
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Correspondence to Tomas Brandejsky .

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Editors and Affiliations

  1. Faculty of Mechanical Engineering, Department of Applied Computer Science, Brno University of Technology, Brno, Czech Republic

    Radek Matoušek

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Brandejsky, T. (2015). Limited Randomness Evolutionary Strategy Algorithm. In: Matoušek, R. (eds) Mendel 2015. ICSC-MENDEL 2016. Advances in Intelligent Systems and Computing, vol 378. Springer, Cham. https://doi.org/10.1007/978-3-319-19824-8_5

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  • DOI: https://doi.org/10.1007/978-3-319-19824-8_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19823-1

  • Online ISBN: 978-3-319-19824-8

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