TY - JOUR
T1 - Testing Different Conjugate Gradient Methods for Large-Scale Unconstrained Optimization
AU -  , Yu-Hong Dai
AU - Ni , Qin
JO - Journal of Computational Mathematics
VL - 3
SP - 311
EP - 320
PY - 2003
DA - 2003/06
SN - 21
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jcm/10259.html
KW - Conjugate gradient methods, Large-scale, Unconstrained optimization, Numerical tests.
AB - <p style="text-align: justify;">In this paper we test different conjugate gradient (CG) methods for solving large-scale unconstrained optimization problems. The methods are divided in two groups: the first group includes five basic CG methods and the second five hybrid CG methods. A collection of medium-scale and large-scale test problems are drawn from a standard code of test problems, CUTE. The conjugate gradient methods are ranked according to the numerical results. Some remarks are given.</p>