A Modified Conjugate Gradient Algorithm with Sufficient Descent

A modification of the Neculai Andrei conjugate gradient algorithm is proposed. Using exact line search, the algorithm reduces to the original version of the Dai and Yuan computational scheme. For inexact line search the algorithm satisfies both sufficient descent and conjugate conditions. A global convergence result is proved when the Wolfe line search conditions are used. Computational results show that this new conjugate gradient algorithm substantially outperforms the Neculai Andrei conjugate gradient algorithm.