Development of a Modified Self-Organizing Migration Optimization Algorithm (MSOMA)

Panteleev A.V.; Rakitianskii V.M.

doi:10.17759/mda.2020100205

Previous issue (2020. Vol. 10, no. 2)

Modelling and Data Analysis

Publisher: Moscow State University of Psychology and Education

ISSN (printed version): 2219-3758

ISSN (online): 2311-9454

DOI: https://doi.org/10.17759/mda

License: CC BY-NC 4.0

Started in 2011

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Modelling and Data Analysis
2020. Vol. 10, no. 2, 62–73
doi:10.17759/mda.2020100205
ISSN: 2219-3758 / 2311-9454 (online)

Development of a Modified Self-Organizing Migration Optimization Algorithm (MSOMA) ³⁴

Panteleev A.V.
Doctor of Physics and Matematics, Professor, Head of the Department of Mathematical Cybernetics, Institute of Information Technologies and Applied Mathematics, Moscow Aviation Institute (National Research University), Moscow, Russia
ORCID: https://orcid.org/0000-0003-2493-3617
e-mail: avpanteleev@inbox.ru

Rakitianskii V.M.
Undergraduate Student of the Institute of Information Technology and Applied Mathematics, Moscow Aviation Institute (National Research University), Moscow, Russia
ORCID: https://orcid.org/0000-0001-7894-7462
e-mail: rymbelv@gmail.com

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The modified self-organizing migration optimization algorithm (MSOMA) based on a self-organizing migration algorithm (SOMA) is suggested. An algorithm for solving the problem of finding the global conditional extremum of the objective function on a given set is developed. Examples illustrating the application of the algorithm and created software are given.

Keywords: global optimization algorithm, migration cycle, population, individual, benchmark problems

Column: Optimization Methods

DOI: https://doi.org/10.17759/mda.2020100205

For Reference

Panteleev A.V., Rakitianskii V.M. Development of a Modified Self-Organizing Migration Optimization Algorithm (MSOMA). Modelirovanie i analiz dannikh = Modelling and Data Analysis, 2020. Vol. 10, no. 2, pp. 62–73. doi:10.17759/mda.2020100205. (In Russ., аbstr. in Engl.)

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