A New Conjugate Gradient Coefficient for Large Scale Nonlinear Unconstrained Optimization

Abstract

Conjugate gradient (CG) methods have played an important role in solving largescale unconstrained optimization due to its low memory requirements and global convergence properties. Numerous studies and modifications have been devoted recently to improve this method. In this paper, a new modification of conjugate gradient coefficient ( k β ) with global convergence properties are presented. The global convergence result is established using exact line searches. Preliminary result shows that the proposed formula is competitive when compared to the other CG coefficients. Mathematics Subject Classification: 65K10, 49M37