【作者】 王勇；

【导师】 薛松涛； 唐和生；

【作者基本信息】 同济大学 ， 风工程， 2008， 硕士

【摘要】 微粒群算法(PSO)是一种新兴仿生智能算法,它源于对鸟群飞行过程中寻找食物的模拟,研究表明其是一种很好的优化算法。它计算高效而且算法本身容易实现,适合求解设计空间不连通的非凸非线性问题。引起了国际上相关领域众多学者的关注和研究,并且已经成功的用于解决很多优化设计问题。本文利用微粒群算法实现对桁架结构的优化,桁架结构优化设计按设计变量类型不同可分为:1、尺寸优化:设计变量为杆件的横截面尺寸,2、形状优化:设计变量为杆件的节点坐标,3、拓扑优化:设计变量为杆件的节点布局、节点间的连接关系。本文的主要工作有以下几个部分:第一章首先介绍了结构优化设计及优化算法的基本概念及其发展,给出了结构优化设计的数学模型,介绍了传统的结构优化算法和现代智能的结构优化算法。第二章详细的阐述了PSO算法的基本理论以及最优化理论,讨论了两种改进的PSO算法,对PSO的收敛性进行了分析。第三章利用PSO解决了桁架优化中的截面优化问题。通过对典型的10-杆平面桁架优化分析,讨论了PSO算法中的参数设置对优化结果的影响。分别对空间桁架在单工况及多工况作用下具有应力及位移约束的优化问题进行研究。第四章利用PSO主要解决桁架优化中的形状优化问题。1、同时考虑桁架截面和节点位置设计变量,采用两种设计变量耦合的方法,克服传统的分层法求解困难且不能得到全局最优解的弱点,解决桁架形状优化问题。2、解决了具有动态约束的结构优化问题,实现了带有局部稳定性约束的桁架形状优化设计。通过算例分析并与已有的文献比较,结果表明PSO能很好的解决桁架形状优化问题。第五章利用PSO对桁架拓扑优化问题做一些简单的探讨,拓扑优化仍然是优化领域的一个难题,本文使用基于截面尺寸拓扑优化模型对算例进行分析,取得了很好的效果。最后,对全文的主要工作和研究成果进行了总结,并指出了有待进一步改进的问题和研究方向。更多还原

【Abstract】 Particle swarm optimization (PSO) is a new type of swarm intelligent bionic algorithm, which is motivated by the behavior of organisms, such as fish schooling and bird flocking. It is characterized as a simple concept, which is both easy to implement and computationally efficient. The algorithm is robust, well suited to handle non-line non-convex design space with discontinuities. PSO has drawn much attentions of researchers and been successfully applied to various optimization problems.In this thesis a PSO algorithm is presented for size, geometry and topology optimal design of truss structures.The main contents of this thesis list as follows:Chapter 1、The basic conception of structural optimization and the development of the traditional and the modern intelligent algorithms are introduced.Chapter 2、A detailed explanation of the basic theories of PSO algorithm is introduced. Two improvements of PSO and the convergence of PSO are analyzed in this chapter.Chapter 3、The PSO is used to solve the Size Optimization problem of truss structure. The performance of the PSO with different setting parameters is discussed through an example of 10-bar truss structure optimal design. In addition, the performance of the PSO for optimal design of a space truss structures with the stress and displacement constrains under one and multi-load cases is discussed. The results show that the proposed algorithm is very efficient for the optimization of truss structure.Chapter 4、The PSO is used to solve the Geometry Optimization problem of truss structure.1、The combination of bar size and node location is developed for the design variables, using the combined variables can overcome the shortcomings of traditional methods, such as decomposition method, which may just find out the local optimal result. 2、Structural geometry optimization under dynamic local stability constraint issolved.Give some examples to testify this algorithm, the results of the examples show that the proposed algorithm and the optimum strategies put forward in this paper are feasible. And the results of the optimization, compared with the existing literature, are satisfying.Chapter 5、The PSO is used to solve the Topology Optimization problem of truss structure. Based on size topology model, then the final topology optimization of thetruss is realized.Chapter 6、The conclusion of the whole paper and it makes a general prediction about the future research work.更多还原