The convergence properties of a new kind of conjugate gradient method for unconstrained optimization

Conjugate gradient (CG) methods are the most prominent technique for solving large-scale unconstrained optimization problems, due to its robustness, low memory requirement, and global convergence properties. Numerous studies and modifications have been carried out recently to improve these methods. In this paper, a new modification of a CG coefficient that possesses the global convergence properties is presented. The global convergence result is validated using exact line search. Several numerical experiments showed that, the proposed formula is found to be robust and efficient when compared to other CG coefficients.