Articles | Volume 16, issue 2
https://doi.org/10.5194/ms-16-673-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Research article
| 
03 Nov 2025
Research article |
| 03 Nov 2025
| 03 Nov 2025
An adaptive improved gray wolf optimization algorithm with dynamic constraint handling for mechanism-constrained optimization problems
Cited articles
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Chakraborty, S., Saha, A., Chakraborty, R., and Saha, M.: An Enhanced Whale Optimization Algorithm for Large Scale Optimization Problems, Knowl-Based. Syst., 233, 107543, https://doi.org/10.1016/j.knosys.2021.107543, 2021.
Chen, G., Tang, Q., Li, X., Wu, W., Wang, K., and Wu, K.: A generic framework for ETW-based dimensional synthesis of parallel mechanism, Proc. Inst. Mech. Eng. C J. Mec. Eng. Sci., 239, 2914–2929, https://doi.org/10.1177/09544062241302205, 2024.
Chen, Q., Sun, J., Palade, V., Wu, X., and Shi, X.: An improved Gaussian distribution based quantum-behaved particle swarm optimization algorithm for engineering shape design problems, Eng. Optimiz., 5, 743–769, https://doi.org/10.1080/0305215x.2021.1900154, 2022.
Chen, X., Ye, C., and Zhang, Y.: Strengthened grey wolf optimization algorithms for numerical optimization tasks and AutoML, Swarm and Evolutionary Computation, 94, 101891, https://doi.org/10.1016/j.swevo.2025.101891, 2025.
