An alternative conjugate gradient approach for large-scale symmetric nonlinear equations

Abstract

Nonlinear conjugate gradient method is a popular approach for solving large-scale unconstrained optimization problems due to its simplest iterative form and low storage requirement. In this article, we proposed a derivative free alternative conjugate gradient approach for solving symmetric nonlinear equations. We show that the proposed method has global convergence properties under appropriate conditions. We also report some numerical results to show its efficiency.