Multi-Objective Optimization of Semi-Submersible Platforms Based on Genetic Algorithm

The main particulars of semi-submersible platforms are the key factor during the design process, which affects the construction cost and hydrodynamic performance. Therefore, it is of great engineering significance to find a design scheme of main particulars that meets the requirements of functional arrangement and construction cost limit and has a relatively good hydrodynamic performance. Aimed at the semi-submersible platform, eight main particulars were selected as input variables to establish the analysis process of grid generation, mass estimation, and hydrodynamic calculation. The hydrodynamic mesh was generated automatically after the parametric modeling of the platform, and the mass and rotational inertia parameters of the platform were obtained through mass estimation. The hydrodynamic performance was calculated by AQWA to obtain the stability, natural periods, and motion RAOs of the platform. Taking a semi-submersible scientific experimental platform as the optimization target, combined with the wave data of the target sea area, the optimization of the main particulars of the platform was carried out based on genetic algorithm. The natural periods and response level of roll, pitch, and heave Motions of the platform were taken as the optimization objectives, and the hydrodynamic performance evaluation function was created through the allocation of the weights of each objective. Meanwhile, with the constraints of the stability and light weight of the platform, the optimization scheme of the main particulars of the platform was obtained, which showed a significant improvement in hydrodynamic performance over the prototype.