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

The optimal design indices of heavy-duty wave compensation parallel mechanisms usually involve trade-off relationships, making multi-objective optimization of great significance for practical engineering applications. 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 NSGA-III algorithm. Firstly, a decision-making model is constructed, incorporating the topological parameters and performance indices of the mechanism. Secondly, an explicit surrogate model is developed to establish the relationship between structural parameters and the physical responses of the system using an ANN, thereby enhancing the computational efficiency of the pose-space traversal of the parallel platform. Finally, the NSGA-III algorithm, integrated with reference points and an interference penalty mechanism, is utilized for high-dimensional parameter optimization, while the technique for order preference by similarity to ideal solution (TOPSIS) is employed to achieve collaborative optimization across different objectives. Comparative results indicate that NSGA-III outperforms the traditional NSGA-II algorithm in terms of evaluation metrics. Compared to the initial baseline design, the optimal solution achieves an 18.12 % improvement in dexterity, an 11.78 % reduction in peak driving force, and a 6.85 % enhancement in the condition number, all while reducing actuator stroke. This study provides a valuable reference for the optimal design and prototype development of heavy-duty wave compensation parallel platforms.