摘要
实际工程中存在大量的离散变量优化问题,基于MSC Nastran优化框架实现新的离散变量算法,有利于新算法本身的推广应用和解决大规模的实际复杂工程问题.通过修改MSC Nastran输入文件的方法实现离散变量的优化算法———GSFP算法.GSFP是基于广义形函数的离散变量优化算法,它将离散变量优化问题转化成连续变量优化问题,通过惩罚等措施使得最优设计结果最终收敛到离散解,该方法能够解决大规模的实际离散变量优化问题.最后以桁架截面选型优化为应用背景,给出GSFP算法实现的基本原理和方法.
There are large number of discrete variable optimization problems in practical engineering. A new discrete variables algorithm can be achieved through the MSC Nastran optimization framework, which is conducive to the promotion and application of the new algorithm and to solve the large-scale complex engineering problems. The discrete variable optimization algorithm-GSFP algorithm by modifying the MSC Nastran input file is implemented. The GSFP is a new discrete variable optimization algorithm based on generalized shape functions, which can translate the discrete variable optimization problem into a continuous variable optimization problem and adopt punishment and other measures. So the optimal design results are eventually converged to the discrete solution. This method can solve large-scale discrete variable optimization problems. The truss sectional selection optimization to introduce the fundamental and implementation methods of achievin~ the GSFP algorithm based on M^t2 N^tr^n ;~ ,,h
出处
《计算机辅助工程》
2013年第A01期463-469,共7页
Computer Aided Engineering
基金
国家重点基础研究发展计划("九七三"计划)(2011CB610304)
国家自然科学基金(10902019
11002031)
中航工业产学研项目(CXY2011DG34)
高档数控机床与基础制造装备科技重大专项资助(2012ZX04010-011)
