WANG J Z, WANG Y, ZHANG P, et al. General fast optimization method for midship section based on Mars2000[J]. Chinese Journal of Ship Research, 2023, 18(5): 133–140. doi: 10.19693/j.issn.1673-3185.02759
Citation: WANG J Z, WANG Y, ZHANG P, et al. General fast optimization method for midship section based on Mars2000[J]. Chinese Journal of Ship Research, 2023, 18(5): 133–140. doi: 10.19693/j.issn.1673-3185.02759

General fast optimization method for midship section based on Mars2000

  •   Objectives  The optimization of midship sections is characterized by the large amount of design variables and the complex constraints. Most relevant research applied the intelligent optimization algorithm embedded with the rule-based calculation program (e.g., Mars2000) from classification society to deal with this issue, which has a large computation cost. Therefore, a general fast optimization method based on sensitivity ranking is proposed for the optimization of midship sections.
      Methods  Firstly, the sensitivity of each constraint about each design variable was evaluated. According to the result of sensitivity, the order of design variables to be modified can be obtained when each constraint is violated. Whether the constraint is only related to local variables or not can be determined as well. During optimization iteration, based on the constraint violation of the current scheme, variable adjustment can be made with the above sensitivity information, and the sensitivity result was updated periodically. Finally, minor adjustment of optimized schemes based on coordinate alternation was employed to further improve the optimization effect.
      Results  The optimization result of an oil tanker midship section shows that the proposed method can achieve a 5.195% reduction of weight.
      Conclusions  Compared with the intelligent optimization algorithm nesting Mars2000 directly, the optimization effect of the proposed method is satisfactory, and the time cost is only 5.58% of the former. The advantage of the proposed method in time cost is quite obvious.
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