摘要
为解决遗传算法优化设计中计算量过大和复合形法常陷入局部最优的问题,综合两种方法的优点,发展了一种引入最优顶点的混合优化方法。该方法首先利用遗传算法全局搜索能力强的特点获得全局最优解在设计空间中的大致位置,然后,将其作为复合形法的初始顶点进行小范围寻优搜索,最终获得全局最优解。文中将遗传算法、复合形法以及该混合方法应用于RAE2822翼型气动优化设计,结果表明,较之遗传算法和复合形法,混合优化方法计算量适中、优化结果好,具有更高的效率。
In order to improve the computational efficiency of genetic algorithm （GA） and avoid getting a local optimum solution in complex method （CM）, these two methods were combined together using their advantages to form a hybrid optimization method based on the best vertex （GA＆CM） in this investigation. In this method, GA was used to get an approximate global optimum solution in design space. Then this solution was taken as the initial vertex of CM to search for a final solution. GA, CM and the hybrid method have been used in the aerodynamic optimization design of RAE2822 airfoil. The results show that the hybrid method is more efficient and can converge to global optimum solution better.
出处
《机械科学与技术》
CSCD
北大核心
2012年第12期2010-2013,共4页
Mechanical Science and Technology for Aerospace Engineering
关键词
遗传算法
复合形法
最优顶点
混合优化方法
翼型优化
genetic algorithm
complex method
best vertex
hybrid optimization method
airfoil optimization
