DOI: 10.17587/prin.14.401-406

Optimization of the Genetic Algorithm using Parallel Computing

V. I. Makarov, Postgraduate Student, Teaching Assistant, Volga Region State University of Telecommunications and Informatics, Samara, 443011, Russian Federation

Corresponding author: Makarov Vadim I. Postgraduate Student, Teaching assistant, Volga Region State University of Telecommunications and Informatics, Samara, 443011, Russian Federation, E-mail: vadimpsuty@gmail.com

In the presented work, a characteristic of the genetic algorithm is given on the example of solving the problem of minimizing the Schwefel function and the possibility of its acceleration using parallelization methods is determined. For the possibility of optimizing the program that implements the algorithm, an analysis of its «slowest» sections and the calculation of an approximate indicator of performance increase are given. As part of the ongoing optimization, it was possible to reduce the execution time of the algorithm by 1.63 times, which corresponds to preliminary calculations.

Keywords: genetic algorithm, genetic algorithm optimization, parallelization of computations, calculation of expected performance

pp. 401–406

For citation:
Makarov V. I. Optimization of the Genetic Algorithm using Parallel Computing, Programmnaya Ingeneria, 2023, vol. 14, no. 8, pp. 401—406. DOI: 10.17587/prin.14.401-406 (in Russian).

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