粒子群算法的最小阻力船型优化研究

Optimization of minimum resistance ship type by particle swarm optimization

阻力是船舶最重要的性能之一,阻力最小是构建船型的首先目标,当前最小阻力船型优化方法存在阻力大等缺陷,为了得到最小阻力的船型,设计基于粒子群算法的最小阻力船型优化方法。首先对当前最小阻力船型优化研究现状进行分析,并建立了最小阻力船型优化的数学模型,然后采用粒子群算法对最小阻力船型优化的数学模型进行求解,找到最小阻力船型优化方案,最后通过与其它方法进行最小阻力船型优化仿真测试,结果表明,相对其它最小阻力船型优化方法,粒子群算法可以更快找到最小阻力船型优化方案,最优船型的阻力大幅度下降,可以应用于实际的最优船型设计中。

Resistance is the most important performance of the ship, and the minimum resistance is the first goal to build the ship type. At present, the minimum resistance ship shape optimization method has large resistance defects. In order to get the minimum resistance ship, the optimization method of minimum resistance ship type based on particle swarm optimization(PSO) is designed. First, the current status of minimum resistance ship model optimization is analyzed, and the mathematical model of minimum resistance ship shape optimization is established. Then the particle swarm optimization algorithm is used to solve the minimum resistance ship model optimization model, and the minimum resistance ship type optimization scheme is found. Finally, the minimum resistance ship model is optimized by other methods. The results show that the particle swarm optimization(PSO) algorithm can find the minimum resistance ship optimization scheme faster than other minimum resistance hull optimization methods, and the resistance of the optimal ship is greatly reduced, and it can be applied to the actual optimal ship design.