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Intellectualization Methods of Population Algorithms of Global Optimization

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Cyber-Physical Systems: Advances in Design & Modelling

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 259))

Abstract

We consider constrained global optimization algorithms that are adaptive (self-adaptive) to the optimization problem being solved. We set tasks of parametric, structural and structural-parametric adaptation of these algorithms. We present the following methods for synthesis of adaptive algorithms for global optimization: tuning methods; control methods; self-control methods. We give some examples of adaptive algorithms and the results of research of their efficiency.

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Authors and Affiliations

  1. Bauman Moscow State Technical University, Moscow, 105005, Russia

    Anatoly Karpenko, Taleh Agasiev & Maksim Sakharov

Authors
  1. Anatoly Karpenko
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  2. Taleh Agasiev
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  3. Maksim Sakharov
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Corresponding author

Correspondence to Anatoly Karpenko .

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Editors and Affiliations

  1. Volgograd State Technical University, Volgograd, Russia

    Alla G. Kravets

  2. Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia

    Alexander A. Bolshakov

  3. Volgograd State Technical University, Volgograd, Russia

    Maxim V. Shcherbakov

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Karpenko, A., Agasiev, T., Sakharov, M. (2020). Intellectualization Methods of Population Algorithms of Global Optimization. In: Kravets, A., Bolshakov, A., Shcherbakov, M. (eds) Cyber-Physical Systems: Advances in Design & Modelling. Studies in Systems, Decision and Control, vol 259. Springer, Cham. https://doi.org/10.1007/978-3-030-32579-4_11

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  • DOI: https://doi.org/10.1007/978-3-030-32579-4_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-32578-7

  • Online ISBN: 978-3-030-32579-4

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