A Test of Non-linear Conjugate Gradient Methods Via Exact Line Search

The conjugate gradient method provides a very powerful tool for solving unconstrained optimization problems. In this paper the non-linear conjugate gradient methods are tested using some benchmark non-polynomial unconstrained optimization functions. The task was accomplished by finding the exact values of the descent also known as the minimizing argument or rather the minimizer in each method. Findings also show that the basic requirement for exact convergence was satisfied by all the methods