Abstract
In this paper, a composite method for bound constrained optimization called Composite Evolutionary Strategy and Differential Evolution (CESDE) is described. This method combines two well-performing methods from the Congress on Evolutionary Computation Competitions. Through numerical investigation on the ICSI’2022 benchmark set, the favourite scheme for combining the two methods was determined, and it was found that CESDE outperforms both of its “parental” methods on all studied instances.
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Acknowledgments
This work was supported by internal grant agency of BUT: FME-S-20-6538 “Industry 4.0 and AI methods”, FIT/FSI-J-22-7980, and FEKT/FSI-J-22-7968.
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Kudela, J., Nevoral, T., Holoubek, T. (2022). Composite Evolutionary Strategy and Differential Evolution Method for the ICSI’2022 Competition. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2022. Lecture Notes in Computer Science, vol 13345. Springer, Cham. https://doi.org/10.1007/978-3-031-09726-3_39
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DOI: https://doi.org/10.1007/978-3-031-09726-3_39
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