Conjugate gradient [CG] methods are considered in solving nonlinear unconstrained optimization problem, because of their simplicity, low memory requirement and global convergence properties. Different reviews and modification have been carried out in order to upgrade the method. In this paper, a new type of CG parameter, which satisfies the sufficient descent condition and global convergences property under exact line search, is proposed. The numerical outcomes indicate that our new modified parameter perform well when compare with other CG parameters for a given standards test function.

No abstract

No abstract

No abstract

In this paper, we suggest a descent modification of the conjugate gradient method which converges globally provided that the exact minimization condition is satisfied. Preliminary numerical experiments on some benchmark problems show that the method is efficient and promising.