基于多目标粒子群算法的船舶主尺度优化设计研究

粒子群优化是一种新兴的进化计算技术。文章基于多目标粒子群优化算法讨论了船舶主尺度论证中的多目标优化和决策问题。对于多目标优化问题,采用基于Pareto占优方法的多目标粒子群算法得到最优解,然后采用距离理想解最近的方法对这些Pareto最优解给出排序。应用文中给出的两个阶段求解方法,对散装货船概念设计阶段主尺度确定的问题进行了分析。结果表明,综合多目标粒子群优化和决策技术,能够迅速、客观地选择合理的船舶主尺度,可以给设计人员提供更多的选择。这种综合方法也能够广泛用于船舶其他设计领域。

Application of Multi-objective Particle Swarm Optimization (MOPSO) in study of ship' s principal parameters

Conceptual design is the least defined stage of the ship design process and seeks to define the basic playloads and ship principal particulars.A two-stage approach for multiobjective optimization study of ship’s principal parameters is proposed here.In the first stage,a Sigma-MOPSO approach is employed to approximate the set of Pareto solutions through an evolutionary process.In the following stage,a decision making skill is adopted to rank these solutions from best to worst.Then the final compromise solution can be achieved.A bulk carrier example is conducted to illustate the analysis process in this study.The result shows that this approach can be widely used for ship design.