Abstract
Optimization is a complex problem in mathematics and engineering applications, which has so far been solved using a variety of approaches based on heuristic methods, methods inspired by nature, methods based on the principles of fuzzy logic, and methods based on rigorous mathematical tools. The most important task is to combine various methods of modeling, optimization, design and management of complex systems within the framework of an integrated approach for a holistic description of the phenomena under study. The objective function of optimization problems combines continuous and discrete variables and various constraints, which indicates its complexity, as well as difficulties in solving such problems. Algorithms that are used in solving optimization problems may suffer from premature convergence when they stop at the optimal solution earlier than required. Based on the problem of premature convergence, a hybrid approach combining a sine–cosine algorithm (SCA) and an artificial bee colony algorithm (ABC) was proposed in the paper. In the proposed algorithm, called the hybrid sine–cosine algorithm (HSCA), both algorithms are executed alternately until the convergence criterion is satisfied.
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References
Permyakova, T., Morozenko, V.: Combined method for solving the backpack problem. In: International Conference Knowledge-Dialogue-Solutions, p. 7 (2017)
Mirjalili, S.: SCA: A sine cosine algorithm for solving optimization problems. Knowl. Based Syst. 120–133 (2016)
Vodolazsky, I.A.: Swarm Intelligence and Its Most Common Methods of Implementation, vol. 4. Young Scientist (2017)
Kureychik, V.V., Zhilenkov M.A.: Bee algorithm for solving problems with an explicit objective function. Inform. Comput. Eng. Eng. Educ. 1(21) (2019)
Deb, K.: An efficient constraint-handling method for genetic algorithms. Comput. Methods Appl. Mech. Eng. 311–338 (2016)
Acknowledgements
The work was supported by the Ministry of Science and Higher Education of the Russian Federation (Grant No. 075-15-2022-1121).
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Ponomareva, K.A., Rozhnov, I.P., Kazakovtsev, L.A. (2024). The Problem of Premature Convergence in Engineering Optimization Problems. In: Vlachos, D. (eds) Mathematical Modeling in Physical Sciences. ICMSQUARE 2023. Springer Proceedings in Mathematics & Statistics, vol 446. Springer, Cham. https://doi.org/10.1007/978-3-031-52965-8_22
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DOI: https://doi.org/10.1007/978-3-031-52965-8_22
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