TY - JOUR
T1 - An Efficient Mixed Conjugate Gradient Method for Solving Unconstrained Optimisation Problems
AU - Mtagulwa , P.
AU - Kaelo , P.
JO - East Asian Journal on Applied Mathematics
VL - 2
SP - 421
EP - 434
PY - 2021
DA - 2021/02
SN - 11
DO - http://doi.org/10.4208/eajam.140720.251220
UR - https://global-sci.org/intro/article_detail/eajam/18642.html
KW - Global convergence, conjugate gradient method, sufficient descent, strong Wolfe conditions.
AB - <p style="text-align: justify;">Conjugate gradient algorithms are most commonly used to solve large scale
unconstrained optimisation problems. They are simple and do not require the computation and/or storage of the second derivative information about the objective function.
We propose a new conjugate gradient method and establish its global convergence under
suitable assumptions. Numerical examples demonstrate the efficiency and effectiveness
of our method.</p>