The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization

摘要

We propose and generalize a new nonlinear conjugate gradient method for unconstrained optimization. The global convergence is proved with the Wolfe linesearch. Numerical experiments are reported which support the theoretical analyses and show the presented methods outperforming CGDESCENT method.