A new non-linear conjugate gradient method based on the Dai-Liao and Kafaki-Ghanbari methods

Abstract

Based on the Dai-Liao and Kafaki-Ghanbari methods, a new non-linear conjugate gradient method is proposed. Under proper conditions, it is briefly shown that our proposed method possess the descent property and generates conjugate directions. We also show that the suggested method with Wolfe line search conditions is globally convergent. Numerical results illustrates that our suggested method can efficiently solve the test problems and therefore is promising.

Keywords

• conjugate gradient method
• descent direction
• unconstrained optimization