In this paper, a new conjugate gradient-like algorithm is proposed to solve unconstrained optimization problems. The step directions generated by the new algorithm satisfy sufficient descent condition independent of the line search. The global convergence of the new algorithm, with the Armijo backtracking line search, is proved. Numerical experiments indicate the efficiency and robustness of the new algorithm.
Kamandi, A., & Amini, K. (2021). A globally convergent gradient-like method based on the Armijo line search. Journal of Mathematical Modeling, 9(4), 665-676. doi: 10.22124/jmm.2021.18854.1612
MLA
Ahmad Kamandi; Keyvan Amini. "A globally convergent gradient-like method based on the Armijo line search". Journal of Mathematical Modeling, 9, 4, 2021, 665-676. doi: 10.22124/jmm.2021.18854.1612
HARVARD
Kamandi, A., Amini, K. (2021). 'A globally convergent gradient-like method based on the Armijo line search', Journal of Mathematical Modeling, 9(4), pp. 665-676. doi: 10.22124/jmm.2021.18854.1612
VANCOUVER
Kamandi, A., Amini, K. A globally convergent gradient-like method based on the Armijo line search. Journal of Mathematical Modeling, 2021; 9(4): 665-676. doi: 10.22124/jmm.2021.18854.1612
)