Articles | Volume 16, issue 2
https://doi.org/10.5194/ms-16-673-2025
https://doi.org/10.5194/ms-16-673-2025
Research article
 | 
03 Nov 2025
Research article |  | 03 Nov 2025

An adaptive improved gray wolf optimization algorithm with dynamic constraint handling for mechanism-constrained optimization problems

Yanhua Lei and Mengzhen Huang

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Short summary
To enhance the convergence speed, accuracy, and high-dimensional constrained optimization problem-solving capability of the traditional gray wolf optimization algorithm, an improved gray wolf optimization algorithm is proposed by integrating an optimal individual memory strategy, a position update strategy with differential variance, and a discrete crossover factor. Experimental results show that the improved algorithm outperforms other comparative ones.
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