| Issue |
ITM Web Conf.
Volume 72, 2025
III International Workshop on “Hybrid Methods of Modeling and Optimization in Complex Systems” (HMMOCS-III 2024)
|
|
|---|---|---|
| Article Number | 05003 | |
| Number of page(s) | 7 | |
| Section | Adaptive Intelligence: Exploring Learning in Evolutionary Algorithms and Neural Networks | |
| DOI | https://doi.org/10.1051/itmconf/20257205003 | |
| Published online | 13 February 2025 | |
Development and analysis of adaptive mutation techniques in genetic algorithms
1 Reshetnev Siberian State University of Science and Technology, Institute of Informatics and Telecommunications, Krasnoyarsk, Russia
2 Siberian Federal University, Institute of Space and Information Technology, Krasnoyarsk, Russia
* Corresponding author: evgenysopov@gmail.com
The proposed adaptive genetic algorithm demonstrates competitive performance, occasionally outperforming the standard approach. Although it shows promising adaptability, further refinements in parameter adjustments and hybridization with other evolutionary techniques could enhance its efficiency, making it a more powerful optimization tool.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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