两类下降的非线性共轭梯度法的全局收敛性

本文在文献1]中提出了一类新共轭梯度法的基础上,给出求解无约束优化问题的两类新的非线性下降共轭梯度法,此两类方法在无任何线搜索下,能够保证在每次迭代中产生下降方向.对一般非凸函数,我们在Wolfe线搜索条件下证明了两类新方法的全局收敛性.

Global Convergence of Two Classes of Descent Nonlinear Conjugate Gradient Methods

Based on a new nonlinear conjugate gradient method proposed in 1], two classes of new nonlinear conjugate gradient methods are proposed to solve general unconstrained optimization problems which produce sufficient descent search direction at every iteration without any line sarch.Under the Wolfe line search, we prove the global convergence of the new methods for general nonconvex functions.