Сибирский журнал науки и технологий
ISSN 2587-6066

Vestnik sibsau
Vestnik sibsau
Vestnik sibsau
Vestnik sibsau

UDK 519.85 Doi: 10.31772/2587-6066-2018-19-3-386-395
A NEW METHOD OF GROUPING VARIABLES FOR LARGE-SCALE GLOBAL OPTIMIZATION PROBLEMS
A. V. Vakhnin*, E. A. Sopov
Reshetnev Siberian State University of Science and Technology, 31, Krasnoyarsky Rabochy Av., Krasnoyarsk, 660037, Russian Federation. *E-mail: alexeyvah@gmail.com
Complexity and dimensionality of real-world optimization problems are rapidly increasing year by year. A lot of real-world optimization problems are complex, thus researchers consider these problems as ‘black box’ models due to the fact that the analysis of the problem is complicated or completely impossible, and partial information about the problem is rarely useful. Heuristic search algorithms have become an effective tool for solving such ‘black box’ optimization problems. In recent decades, many researchers have designed a lot of heuristic algorithms for solving largescale global optimization (LSGO) problems. In this paper, we proposed an innovative approach, which is called DECC-RAG. The approach is based on an original method of grouping variables (random adaptive grouping (RAG)) for cooperative cooperation framework. The RAG method uses the following idea: after a specified number of fitness evaluation in the cooperative coevolution with Информатика, вычислительная техника и управление 387 the SaNSDE algorithm, we choose a half of subcomponents with the worst fitness values and randomly mix indices of variables in these subcomponents. We have evaluated the DECC-RAG algorithm with 20 LSGO benchmark problems from the IEEE CEC’2010 and on 15 LSGO benchmark problems from the IEEE CEC’2013 competitions. The dimensionality of benchmark problems was equal to 1000. The experimental results have shown that the proposed method of optimization (DECC-RAG) outperforms some well-known algorithms on the large-scale global optimization problems from LSGO CEC’2010 and LSGO CEC’2013.
Keywords: optimization, large-scale, evolution algorithms, cooperative coevolution.
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Vakhnin Alexey Valeryevich – Master’s Degree student, Reshetnev Siberian State University of Science and Technology. Е-mail: alexeyvah@gmail.com.

Sopov Evgenii Aleksandrovich – Cand. Sc., Docent, Docent of Department of System analysis and operations research, Reshetnev Siberian State University of Science and Technology. Е-mail: evgenysopov@gmail.com.


  A NEW METHOD OF GROUPING VARIABLES FOR LARGE-SCALE GLOBAL OPTIMIZATION PROBLEMS