J Shanghai Jiaotong Univ Sci ›› 2022, Vol. 27 ›› Issue (3): 346-355.doi: 10.1007/s12204-022-2445-2

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  • 收稿日期:2020-11-12 出版日期:2022-05-28 发布日期:2022-06-23

Multiobjective Optimization of Hull Form Based on Global Optimization Algorithm

LIU Jiea (刘 洁), ZHANG Baojib∗ (张宝吉)   

  1. (a. Merchant Marine College; b. College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, China)
  • Received:2020-11-12 Online:2022-05-28 Published:2022-06-23

Abstract: Rankine source method, optimization technology, parametric modeling technology, and improved mul tiobjective optimization algorithm were combined to investigate the multiobjective optimization design of hull form. A multiobjective and multilevel optimization design framework was constructed for the comprehensive navigation performance of ships. CAESES software was utilized as the optimization platform, and nondominated sorting genetic algorithm II (NSGA-II) was used to conduct multiobjective optimization research on the resis tance and sea-keeping performance of the ITTC Ship A-2 fishing vessel. Optimization objectives of this study are heave/pitch response amplitude and wave-making resistance. Taking the displacement and the length between perpendiculars as constraints, we optimized the profile of the hull. Analytic hierarchy process (AHP) and tech nique for order preference by similarity to ideal solution (TOPSIS) were used to sort and select Pareto solutions and determine weight coefficient of each navigation performance objective in the general objective. Finally, the hydrodynamic performance before and after the parametric deformation of the hull was compared. The results show that both the wave-making resistance and heave/pitch amplitude of the optimized hull form are reduced, and the satisfactory optimal hull form is obtained. The results of this study have a certain reference value for the initial stage of multiobjective optimization design of hull form.

Key words: multiobjective optimization, Rankine source method, global optimization algorithm, nondominated sorting genetic algorithm II (NSGA-II)

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