IJPAM: Volume 106, No. 1 (2016)

GLOBAL OPTIMIZATION OF FUNCTIONS OF
SEVERAL VARIABLES USING PARALLEL TECHNOLOGIES

Igor Grigoryev$^1$, Svetlana Mustafina$^2$
$^{1,2}$Sterlitamak Branch of the Bashkir State University
37, Lenin Avenue, Sterlitamak city, 453103, Russia;


Abstract. In this paper, on the basis of the method particle swarm optimization was developed the algorithm of the parallel search of global extremum. In the system of parallel programming on C language implemented method of particle swarm for the global minimization of functions. The performance of the parallel method was tested for two famous benchmark optimization problems (Styblinski Tang function and Rastrigin function) and compared with the results obtained by employing the sequential method. Conducted research on the effectiveness of parallelization has shown the advantage of the parallel algorithm.

Received: December 7, 2015

AMS Subject Classification: 65Y05, 68W10, 52A40

Key Words and Phrases: global extremum, the method of particle swarm, parallel computing, Nvidia CUDA

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DOI: 10.12732/ijpam.v106i1.24 How to cite this paper?

Source:
International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2016
Volume: 106
Issue: 1
Pages: 301 - 306


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