Testing different conjugate gradient methods for large-scale unconstrained optimization. (English) Zbl 1041.65048

Dai, Yuhong; Ni, Qin

J. Comput. Math. 21, No. 3, 311-320 (2003).

Summary: 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.

MSC:

65K05	Numerical mathematical programming methods
90C06	Large-scale problems in mathematical programming
90C30	Nonlinear programming

Keywords:

steepest descent method; conjugate gradient methods; large-scale unconstrained optimization problems; numerical results

Software:

L-BFGS; CUTEr