Research Article of Advances in Research and Reviews
Principal optimization of semi-submersible support platform based on multi-island genetic algorithm
Changyi He1*, Ji Zeng1, Zhuyun Shao1, Shifeng Lu1, Bowen Jin1
1Shanghai Maritime University, Merchant Marine College, Shanghai, 201306, China.
Aiming at the conceptual design stage of semi-submersible support platform, the optimal primary scale scheme is designed. Latin hypercube design is adopted to sample the sample space. At the same time, SESAM software is used for parametric modeling based on sample point parameters to obtain the model of all schemes. According to the existing data of semi-submersible platforms, the main scale constraints of platforms are determined, and the mathematical model with the minimum heave, trim and roll response as the objective function is established. The multi-island genetic algorithm was used to optimize the main scale of the supporting platform model, and the scheme with the highest stability and suitable displacement was selected. The results show that the model and algorithm are feasible, and the smallest scale scheme of each response can be obtained under the constraint conditions. The multi-island genetic algorithm is proposed to optimize the primary scale of the platform, which has a strong reference value for the determination of the primary scale scheme in the conceptual design stage of the platform.
Keywords: Multi-island genetic algorithm; Latin hypercube design; Principal dimensions; Optimize
How to cite this article:
Changyi He, Ji Zeng, Zhuyun Shao, Shifeng Lu, Bowen Jin. Principal optimization of semi-submersible support platform based on multi-island genetic algorithm. Advances in Research and Reviews, 2020; 1:8. DOI: 10.28933/arr-2020-08-0205
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