Articles | Volume 17, issue 2
https://doi.org/10.5194/ms-17-783-2026
https://doi.org/10.5194/ms-17-783-2026
Research article
 | 
28 Jul 2026
Research article |  | 28 Jul 2026

Optimal design and validation of a heavy-duty wave compensation parallel platform utilizing the NSGA-III algorithm

Tianzhong Huang, Renjie Luo, Lifeng Mao, Jia Wang, Fei Zhou, and Guoxing Zhang

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Cited articles

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Bhosekar, A. and Ierapetritou, M.: Advances in surrogate based modeling, feasibility analysis, and optimization: A review, Comput. Chem. Eng., 108, 250–267, https://doi.org/10.1016/j.compchemeng.2017.09.017, 2018. 
Briot, S. and Khalil, W.: Dynamics of parallel robots: From rigid bodies to flexible elements, Springer, https://doi.org/10.1007/978-3-319-19788-3, 2015. 
Chen, W., Wen, Y., Tong, X., Lin, C., Li, Jiang., Wang, S., Xie, W., Mao, L., Zhao, X., Zhang, W., and Gao, F.: Dynamics modeling and modal space control strategy of ship-borne Stewart platform for wave compensation, J. Mech. Robot., 15, 041015, https://doi.org/10.1115/1.4062177, 2023. 
Chugh, T., Sindhya, K., Hakanen, J., and Miettinen, K.: A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms, Soft Comput., 23, 3137–3166, https://doi.org/10.1007/s00500-017-2965-0, 2017. 
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Short summary
This study proposes a multi-objective optimization approach tailored for a heavy-duty wave compensation parallel platform, which integrates an artificial neural network (ANN) surrogate model with an enhanced non-dominated sorting genetic algorithm III (NSGA-III).
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