【作者】 陈亚洲；

【导师】 高亮；

【作者基本信息】 华中科技大学 ， 工业工程， 2007， 硕士

【摘要】 产品的设计水平和能力是衡量一个国家或者地区工业创新能力和竞争能力的决定性因素。复杂产品的设计是一个多学科交叉、综合设计、优化的过程。多学科设计优化能够满足复杂工程系统的设计优化的需求,可以有效地解决大规模复杂工程系统的设计问题,它综合集成了设计方法、设计知识、现代信息技术,是一种面向大系统设计的方法。本文对协同优化方法进行了研究,改进了协同优化方法,并将其应用于工程实例。首先,深入了解了国内外学者在多学科设计优化(MDO)方面的工作和成果,对多学科设计优化技术进行详细的综述;其次,分析了传统的协同优化方法的计算特性。分别从数学原理和数学算例对其进行分析和探讨,指出了传统协同优化方法计算困难的根本原因,并给出相应的改进方向;然后针对传统协同优化方法的计算困难和改进方向,将粒子群优化算法(PSO)引入协同优化方法,通过变换系统级框架,提出一种基于PSO的改进协同优化方法PSO-CO,并结合实际的数学算例和工程应用实例,对PSO-CO进行验证。结果表明, PSO-CO具有较好的计算性能;最后,针对设计的四个基本原则,对协同优化方法的结构框架进行变换,提出一种新型的协同优化模式,同时采用粒子群优化算法作为其内部协同算法的优化器,并以MDO的标准算例进行测试。结果表明,引入PSO的协同优化新模式具有较好的鲁棒性能,可应用于实际问题。更多还原

【Abstract】 The achievement and capability of product designing are key factors to the innovative and competitive power of a nation’s or an area’s industry. Designing complex product is a multidisciplinary-crossed, integrated designing and optimization process. Multidisciplinary Design Optimization (MDO) meets the requirements of the design optimization and development of the engineering system. MDO is a kind of design methodology integrating design method, design knowledge and modern information technology which can solve the designing problem of the cosmically complex engineering system.The purpose of this paper is to analyze and improve the method of the MDO - the Collaborative Optimization (CO), and to apply the CO to the engineering projects.Firstly, I reviewed all the work and achievements of scholars around the world in the research of MDO, and described the content of the MDO technology in detail.Secondly, this thesis analyzed the computation characteristics of the original CO method and deeply discussed the computation difficulties of the CO method from different aspects. And by dint of math example, it also pursued the sources of the computing hardness of CO methods and makes a simple evaluation and improving direction. Furthermore, Considered the computing complexity caused by the original CO method and the improvement direction, this article applied a new creationary evolutionary method - Particle Swarm Optimization(PSO)to the traditional CO method. By modifying the system frame, this paper presents a new structure named improved Collaborative Optimization which is based on Particle Swarm Optimization (PSO-CO), this novel method is tested by the MDO standard examples. The computation results demonstrate that the proposed PSO-CO has better calculation ability.Finally, according to the four designing principles, by transforming the compute structure of CO, this section describes a novel CO mode which involves the PSO evolutionary algorithm as an optimizer, and the new-model method proposed in this thesis is also tested by MDO standard examples. The computation result illustrates that the new-mode CO method is robust and has its validity in applying to the practical design.更多还原