摘要
将最速下降法与共轭梯度法有机结合起来,构造出一种混合优化算法,并证明其全局收敛性.这种混合优化算法结合了共轭梯度法和最速下降法产生搜索方向,既提高了共轭梯度算法的收敛速度,又解决了目标函数的等值线是扁长椭球时,最速下降法下降缓慢的问题,具有收敛速度快、收敛范围大、适应面广等特点.文中的算法实例表明,混合算法与单纯的共轭梯度法相比,效果更优.
Based on the steepest descent method and the conjugate gradient method, a hybrid algorithm is proposed in this paper, and its global convergence is proved. The hybrid algorithm raises the convergence rate of the conjugate gradient method and solves the problem for which the convergence rate of the steepest descent method get slower when the iso- pleth of goal function is oblong. In conclusion, the method has features with quick convergence rate, large convergence range and wide accommodation compared with the conjugate gradient method, the hybrid algorithm method has a better result in the example.
出处
《华侨大学学报（自然科学版）》
CAS
北大核心
2007年第2期124-126,共3页
Journal of Huaqiao University(Natural Science)
基金
福建省自然科学基金资助项目(A0540002)
关键词
最速下降法
共轭梯度法
混合算法
全局收敛性
the steepest descent method
conjugate gradient method
hybrid algorithm
global convergence
