广义Wolfe线搜索下共轭梯度法的全局收敛性

摘要

In the ordinary circumstances,conjugate gradient method is the effective algorithm which solves the large-scale restraint question. Different parameter selected constructs different conjugate gradient method. A novel conjugate gradient method for solving nonlinear unconstrained optimization problem is studied, the sufficient descent property and global convergence of the new conjugate gradient method with general Wolfe line search are proved.%共轭梯度法是求解大规模约束问题的有效算法,不同的参数选取构成不同的共轭梯度法.通过研究一个新的求解无约束最优化问题的共轭梯度法,证明该公式在广义Wolfe线搜索下是具有充分下降性,并且是全局收敛的.