摘要
基于文献[6]中的βb k的构造方法,提出了一种新的谱共轭梯度法,证明了该方法不依赖于任何线搜索具有充分下降性,在Armijo线搜索下证明了算法具有全局收敛性。数值试验结果表明:在Armijo线搜索下,该方法明显优于SFRA、SPRPA算法。
Based on the construction method of literature [ 6 ], this paper proposes a new spectrum conjugate gradi- ent method, which shows that the method is not dependent on any line search and has enough drop characteristic. The algorithm is proved to have global convergence under Armijo line search. Numerical test results show that:, this method under Armijo line search is superior to SFRA, SPRPA algorithm.
出处
《太原科技大学学报》
2013年第6期464-467,共4页
Journal of Taiyuan University of Science and Technology
关键词
无约束优化
谱共轭梯度法
ARMIJO搜索
全局收敛性
unconstrained optimization, spectral conjugate gradient method, Armijo search, global convergence