A modified nonlinear conjugate gradient method for unconstrained optimization

Nonlinear conjugate gradient method holds an important role in solving large scale unconstrained optimization problems. Their simplicity, low memory requirement, and global convergence stimulated a massive study on the method. Numerous modifications have been done recently to improve its performance. In this paper, we proposed a new formula for the conjugate gradient coefficient k  that generates the descent search direction. In addition, we...