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Numerical Modelling of Mean-Field Game Epidemic

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Optimization and Applications (OPTIMA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14395))

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Abstract

The mean-field game model of infectious disease local propagation is formulated and solved numerically considering social behavior of modelled population. The numerical algorithm based on collocation method is proposed. As a result of numerical modelling with specific assumptions about population, its movement cost, knowledge about infected group, initial distribution and its optimal behavior is acquired and discussed.

Supported by the Mathematical Center in Akademgorodok.

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Acknowledgements

The work is supported by the Russian Science Foundation, project No. 23-71-10068.

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Authors and Affiliations

  1. Institute of Computational Mathematics and Mathematical Geophysics SB RAS, Novosibirsk, Russia

    Andrei Neverov

  2. Sobolev Institute of Mathematics SB RAS, Novosibirsk, Russia

    Olga Krivorotko

Authors
  1. Andrei Neverov
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  2. Olga Krivorotko
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Corresponding author

Correspondence to Andrei Neverov .

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Editors and Affiliations

  1. FRC CSC RAS, Moscow, Russia

    Nicholas Olenev

  2. FRC CSC RAS, Moscow, Russia

    Yuri Evtushenko

  3. University of Montenegro, Podgorica, Montenegro

    Milojica Jaćimović

  4. Krasovsky Institute of Mathematics and Mechanics, Ekaterinburg, Russia

    Michael Khachay

  5. FRC CSC RAS, Moscow, Russia

    Vlasta Malkova

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Neverov, A., Krivorotko, O. (2023). Numerical Modelling of Mean-Field Game Epidemic. In: Olenev, N., Evtushenko, Y., Jaćimović, M., Khachay, M., Malkova, V. (eds) Optimization and Applications. OPTIMA 2023. Lecture Notes in Computer Science, vol 14395. Springer, Cham. https://doi.org/10.1007/978-3-031-47859-8_15

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  • DOI: https://doi.org/10.1007/978-3-031-47859-8_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47858-1

  • Online ISBN: 978-3-031-47859-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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