A modified Dai-Liao-type conjugate gradient method for unconstrained optimization

Abstract

Conjugate gradient (CG) methods have proved over the years to be efficient for solving large-scale unconstrained optimization problems. In this paper, a Dai-Liao (DL)-type CG method is proposed using proper combination of the update parameters of LS-CG and AyO-CG methods. Under some certain assumptions, descent and convergence properties were established. Preliminary results illustrate that the new schemes can compete favorably well with some existing ones, when subjected to numerical test under Dolan and More performance profile tools.