Robust Parameters for Conjugate Gradient Method in Unconstrained Optimization

The conjugate gradient approach is used to resolve unrestricted optimization problems, uses the quadratic model for the objective function to generate a new coefficient conjugate. The algorithms are globally convergent and have the necessary descent property. In numerical testing, the new approach has shown to be quite effective. The results show that the novel conjugate gradient approach best the conventional FR conjugate gradient method.