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The Stochastic Coverings Algorithm for Solving Applied Optimal Control Problems

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Mathematical Optimization Theory and Operations Research (MOTOR 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1090))

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Abstract

The paper considers a heuristic method for a global extremum search in an optimal control problem based on the idea of covering a reachable set by n-dimensional balls, including the built-in mechanisms for Lipschitz constant estimating of the objective functional. A step-by-step description of the coverage algorithm and the proposed method for generating start and auxiliary controls are presented. The proposed technique was used for solving applied optimal control problems: the problem of investment programs in Buryatia Republic and the problem of restoring the Black Lands in Kalmykia.

Supported by Russian Foundation for Basic Research, grant No. 17-07-00627.

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Author information

Authors and Affiliations

  1. Matrosov Institute for System Dynamics and Control Theory SB RAS, Irkutsk, Russia

    Alexander Gornov, Tatiana Zarodnyuk, Anton Anikin & Pavel Sorokovikov

Authors
  1. Alexander Gornov
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  2. Tatiana Zarodnyuk
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  3. Anton Anikin
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  4. Pavel Sorokovikov
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Corresponding author

Correspondence to Tatiana Zarodnyuk .

Editor information

Editors and Affiliations

  1. Sobolev Institute of Mathematics, Novosibirsk, Russia

    Igor Bykadorov

  2. University of Greenwich, London, UK

    Vitaly Strusevich

  3. University of Aveiro, Aveiro, Portugal

    Tatiana Tchemisova

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Gornov, A., Zarodnyuk, T., Anikin, A., Sorokovikov, P. (2019). The Stochastic Coverings Algorithm for Solving Applied Optimal Control Problems. In: Bykadorov, I., Strusevich, V., Tchemisova, T. (eds) Mathematical Optimization Theory and Operations Research. MOTOR 2019. Communications in Computer and Information Science, vol 1090. Springer, Cham. https://doi.org/10.1007/978-3-030-33394-2_37

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  • DOI: https://doi.org/10.1007/978-3-030-33394-2_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33393-5

  • Online ISBN: 978-3-030-33394-2

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