Cite this article as:

Savin A. N., Druzhinin I. ., Eroftiev A. A. The Application of a Genetic Algorithm to Global Optimization Problem Solving on Parallel and Distributed Computing Systems. Izv. Saratov Univ. (N. S.), Ser. Math. Mech. Inform., 2013, vol. 13, iss. 1, pp. 99-109. DOI: https://doi.org/10.18500/1816-9791-2013-13-1-1-99-109

Language: 
Russian
Heading: 
Computer Sciences
UDC: 
681.3.06, 681.322

The Application of a Genetic Algorithm to Global Optimization Problem Solving on Parallel and Distributed Computing Systems

Authors: 
Savin Aleksandr Nikolaevich, Saratov State University 1, Saratov State University, Russia, 410012, Saratov, Astrahanskaya st., 83 , savinan@info.sgu.ru
Druzhinin Igor Vyacheslavovich, Moscow State Technical University named after N. E. Bauman, ул. 2-я Бауманская, 5, стр. 1, Москва, г. Москва, Россия , druzhininiv@gmail.com
Eroftiev Andrei Aleksandrovich, Saratov State University 1, Saratov State University, Russia, 410012, Saratov, Astrahanskaya st., 83 , eroftiev.andrey@gmail.com
Abstract: 

This article presents the results of the adaptation of method of searching the global minimum of multiextremal criterion function of multiple variables with constraints based on genetic algorithm for parallel and distributed computing systems. Two variants of genetic algorithm parallelization are proposed. The reliability and performance of parallel versions of an algorithm, depending on its parameters and the number of nodes in parallel computer system is investigated. The reliability of finding the global minimum of criterion function in a small amount of time with proposed parallel variants of genetic algorithm is represented.

Key words: 
global optimization, genetic algorithm, multiextreme criterion function, parallel computing system
DOI: 
https://doi.org/10.18500/1816-9791-2013-13-1-1-99-109
References
  1. Орлянская И. В. Современные подходы к построению методов глобальной оптимизации // Электронный журнал «Исследовано в России». С. 2097–2108. URL : http://zhurnal.ape.relarn.ru/articles/2002/189.pdf (дата обращения : 2.12.2011). [Orlyanskaya I.V. Modern approaches to global optimization methods building //Online magazine «Issledovano v Rossii». P. 2097–2108. URL : http://zhurnal.ape.relarn.ru/articles/2002/189.pdf (last checked : 2.12.2012).]
  2. Банди Б. Методы оптимизации. Вводный курс. М. : Радио и связь, 1988. 127 с. [Brian D. Bunday Basic Optimisation Methods. London : Edward Arnold, 1984. 128 p.]
  3. Панченко Т. В. Генетические алгоритмы : учеб.-метод. пособие / под ред. Ю. Ю. Тарасевича / Астрахан. ун-т. Астрахань, 2007. 87 с. [Panchenko T.V. Genetic algorithms : the methodical manual / Ed. by Yu. Yu. Tarasevich / Astrakhan. Univer. Astrakhan, 2007. 87 p.]
  4. Калиткин Н. Н. Численные методы. М. : Наука, 1978. 512 с. [Kalitkin N. N. Numerical methods. Moscow : Nauka, 1978. 512 p.]
  5. Eroftiev A. A., Timofeeva N. E., Savin A. N. Parallel Computing in Application to Global Optimization Problem Solving // Grid and Visualization Systems : MIPRO, 2011 Proc. of the 34th Intern. Convention. Zagreb, Croatia : DENONA, 2011. P. 185–190.
Full text:
download
79