PSO算法在油船双底结构优化设计中的应用研究  

Optimizing the design of the double bottom structure of an oil tanker using a particle swarm optimization algorithm

作　　者：秦洪德[1] 石丽丽[1] 

机构地区：[1]哈尔滨工程大学船舶工程学院,黑龙江哈尔滨150001

出　　处：《哈尔滨工程大学学报》2010年第8期1007-1011,共5页Journal of Harbin Engineering University

基　　金：111计划基金资助项目(B07019);哈尔滨工程大学基础研究基金资助项目(002010260718)

摘　　要：为了研究粒子群优化(PSO)算法用于解决大型复杂结构的优化设计问题的有效性,分别采用基本PSO算法、标准PSO算法与遗传算法(GA)对某一大型油船双层底结构优化设计问题进行了求解.优化过程中双层底结构的响应分析计算过程采用正交异性组合板理论实现.将这3种优化算法的计算结果进行对比分析表明,与基本PSO算法和GA算法相比较,标准PSO算法的收敛速度最快,且能够获得该问题的全局最优解.研究结果表明,基本PSO算法可有效应用于解决如船体双层底等大型复杂结构优化设计问题.In order to see if the particle swarm optimization（PSO） algorithm can be adapted to optimize the design process for large and complex structures,the authors first applied basic PSO,then standard PSO and finally a genetic algorithm（GA） to optimize the double bottom structure of a very large crude carrier（VLCC）.The double bottom structure was simplified into an orthotropic plate when performing the structural response analysis.The comparison of these three optimization algorithms showed that the convergence of standard PSO was faster than both basic PSO and the GA,especially in the preliminary stage of optimization iteration,and it obtained the global best solution.PSO is an effective optimization algorithm and is suitable for optimization of large and complicated structures.

关 键 词：粒子群优化(PSO) 离散变量 结构优化设计 双层底结构 正交异性板 收敛速度 

分 类 号：U662.2[交通运输工程—船舶及航道工程]