A SURVEY OF NONLINEAR CONJUGATE GRADIENT METHODS ∗ 1. Introduction.
Conjugate gradient (CG) methods comprise a class of uncon- Page 1 A SURVEY OF …

Conjugate gradient methods are widely used for unconstrained optimization, especially
large scale problems. The strong Wolfe conditions are usually used in the analyses and …

Optimization Theory and Methods can be used as a textbook for an optimization course for
graduates and senior undergraduates. It is the result of the author's teaching and research …

This book is on conjugate gradient methods for unconstrained optimization. The concept of
conjugacy was introduced by Magnus Hestenes and Garrett Birkhoff in 1936 in the context of …

In this paper, we propose a modified Polak–Ribière–Polyak (PRP) conjugate gradient
method. An attractive property of the proposed method is that the direction generated by the …

Conjugate gradient methods are a class of important methods for solving linear equations
and for solving nonlinear optimization. In this article, a review on conjugate gradient …

Recently, we propose a nonlinear conjugate gradient method, which produces a descent
search direction at every iteration and converges globally provided that the line search …

In this paper, we are concerned with the conjugate gradient methods for solving
unconstrained optimization problems. It is well-known that the direction generated by a …

In this paper, a new conjugate gradient formula βk∗ is given to compute the search
directions for unconstrained optimization problems. General convergence results for the …

Recently, important contributions on convergence studies of conjugate gradient methods
were made by Gilbert and Nocedal SIAM J. Optim., 2 (1992), pp. 21--42. They introduce a" …