Abstract
The optimal control problem is well known long time ago, but there is no a general numerical method for it. More precisely researchers try always to solve this problem various numerical methods. Recently it was established, that if the optimal control problem has phase constraints included in quality criterion, then a functional is multimodal and this optimization problem belongs to global class optimization. Therefore, to solve the optimal control problem it is better to use evolutionary algorithms. But this proposition doesn’t give useful information for researcher, because now there are huge quantity evolutionary algorithms. In this paper the best evolutionary algorithm for the optimal control problem is proposed. It is constructed on the base three evolutionary algorithms, genetic algorithm, particle swarm optimization, and grey wolf optimizer. It is shown computational experiments, where this hybrid algorithm is compared with everyone from listed above on the complex problem with phase constraints.
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Diveev, A. (2023). Hybrid Evolutionary Algorithm for Optimal Control Problem. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2022. Lecture Notes in Networks and Systems, vol 543. Springer, Cham. https://doi.org/10.1007/978-3-031-16078-3_50
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DOI: https://doi.org/10.1007/978-3-031-16078-3_50
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