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Global convergence limits of differential evolution algorithm

• Roman Knobloch
• Jaroslav Mlynek

(2024). ECMS 2024, 38th Proceedings
Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation.
DOI: http://doi.org/10.7148/2024
ISSN: 2522-2422 (ONLINE)
ISSN: 2522-2414 (PRINT)
ISSN: 2522-2430 (CD-ROM)
ISBN: 978-3-937436-84-5
ISBN: 978-3-937436-83-8 (CD) Communications of the ECMS Volume 38, Issue 1, June 2024, Cracow, Poland June 4th – June 7th, 2024

https://doi.org/10.7148/2024-0387

Roman knobloch, Jaroslav mlynek (2024). Global Convergence Limits of Differential Evolution Algorithm, ECMS 2024, Proceedings Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation. doi:10.7148/2024-0387

In a recent period, evolutionary optimization techniques have been increasingly utilized for solving technical and scientific optimization tasks. The differential evolution algorithm is one of the most used optimization tools. This specific algorithm is often and in many published sources classified as a global optimizer. Such statements indicate that the differential evolution algorithm can identify the global minimum of a specific cost function.

In the article, we demonstrate rigorously and in a simple way that in some special circumstances, this algorithm fails and is prone to premature convergence to a local minimum of the cost function.