摘要
利用KS函数的凝聚特性,将常见的多约束机械优化设计问题中的全部或部分约束凝聚为一个近似的、拟合精度仅由一个参数控制的约束,然后再对此缩减后的优化问题,选用适当的约束优化方法求解。应用KSr磨光函数和内点极径扫描法给出的此方法低维可行域几何解释,表明了约束条件集的凝聚结果。实例证明,由于缩减了求解规模,此方法收敛稳定且速度快。
A new method for solving multi-constraints optimum problem is presented, Using the characteristic of KS functions, all constraints or some constraints are numerically approximated into only one constraint whose precision is controlled by one parameter. Then the problem is solved by an appropriate constraint optimum method. Also a geometric explanation of low-dimension available field of the method is given by using KS smooth function and interior radius vector sweeping method. This geometric explanation shows the condensing result of the constraint condition set. Examples prove that the method is constantly convergent and easy to be completed because of the scale-down of calculation process
出处
《现代制造工程》
CSCD
2005年第9期1-5,共5页
Modern Manufacturing Engineering
基金
国家"863"高技术研究发展计划资助(2001AA411110)
关键词
多约束优化问题
KS函数
可行域
凝聚算法
Multi-constraints optimum problem KS function Available field Condensing algorithm
