Izvestiya of Saratov University.

Mathematics. Mechanics. Informatics

ISSN 1816-9791 (Print)
ISSN 2541-9005 (Online)


For citation:

Vysotskii A. V., Tarakanov A. S., Sholomov K. I., Timofeeva N. E., Eroftiev A. A. The Effectiveness Analysis of Several Parallel Algorithms Based on Simulated Annealing Method of Global Optimization Problem Solving. Izvestiya of Saratov University. Mathematics. Mechanics. Informatics, 2013, vol. 13, iss. 3, pp. 87-95. DOI: 10.18500/1816-9791-2013-13-3-87-95

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Published online: 
27.08.2013
Full text:
(downloads: 169)
Language: 
Russian
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UDC: 
681.3.06, 681.322

The Effectiveness Analysis of Several Parallel Algorithms Based on Simulated Annealing Method of Global Optimization Problem Solving

Autors: 
Vysotskii Aleksandr Vitalevich, Saratov State University
Tarakanov Aleksei Sergeevich, Saratov State University
Sholomov Konstantin Igorevich, Saratov State University
Timofeeva Nadezhda Evgen'evna, Saratov State University
Eroftiev Andrei Aleksandrovich, Saratov State University
Abstract: 

This article presents the results of the development of a parallel computing system and testing its capabilities applied to solving scientific and educational problems. Three parallel variants of the simulated annealing algorithm are proposed and implemented for multiextreme criterion function of two variables with explicit constraints. The reliability and performance of parallel versions of the algorithm, depending on their parameters and the number of working nodes in parallel computing system, is investigated. It is shown that proposed parallel variants of simulating annealing algorithm allow successful finding the global minimum of multiextreme criterion function.

References: 
  1. Lopatin A. S. Simulated Annealing. Stokhasticheskaia optimizatsiia v informatike : mezhvuz. sb. [Stochastic Optimization in Informatics]. St. Petersburg, 2005, iss. 1, pp. 133–149 (in Russian).
  2. Savin A. N, Timofeeva N. E. Using Optimization Algorithm Based on Simulated Annealing on Parallel and Distributed Computing Systems. Izv. Sarat. Univ., N.S., Ser. Math. Mech. Inform., 2012, vol. 12, iss. 1, pp. 110– 116 (in Russian).
  3. Kirkpatrick S. A., Gelatt C. D., Vecchi M. P. Optimization by simulated annealing. Science, N.S., 1983, vol. 220, no. 4598, pp. 671–680.
Received: 
20.02.2013
Accepted: 
27.07.2013
Published: 
30.08.2013
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