基于改进粒子群−模拟退火算法的集装箱船结构优化方法

A structural optimization method for container ships based on an improved particle swarm-simulated annealing algorithm

  • 摘要:
    目的 旨在研究集装箱船典型结构的多目标优化问题。
    方法 首先建立船舶结构构件库,实现优化变量的离散化。其次提出一种动态调整优化参数的改进PSO-SA算法(IPSO-SA),实现快速搜索单目标优化问题的全局最优解。然后引入Pareto支配,构建多目标优化算法MOPSO-SA。
    结果 以集装箱船平行中体结构优化为例,利用构件库建立参数化模型并实施优化,实现减重26.051%,且在结构重量减少14.111%的同时,重心垂向高度降低12.951%。
    结论 研究成果在提升设计方案的经济性的同时,显著改善了集装箱船的稳性。

     

    Abstract:
    Objective To investigate the multi-objective optimization problem of typical container ship structures.
    Method This paper first established a ship structural component library to discretize the optimization variables. Next, an improved PSO-SA algorithm (IPSO-SA) with dynamically adjusted optimization parameters was proposed. This method facilitates the rapid identification of the global optimal solution for single-objective optimization problems. Then, by introducing Pareto dominance, a MOPSO-SA algorithm for multi-objective optimization was developed.
    Results Taking the parallel middle body structure optimization of a container ship as an example, the parametric model of the structural components was constructed with the established component library, and the proposed optimization algorithm was applied. This approach resulted in a 26.051% reduction in weight, a 14.111% decrease in structural weight, and a 12.951% reduction in the vertical center of gravity.
    Conclusion The research not only improved the economic efficiency of the original design but also significantly enhanced the stability of the container ship.

     

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