We suggest a conjugate gradient (CG) method for solving symmetric systems of nonlinear
equations without computing Jacobian and gradient via the special structure of the …

In this paper, using approximate gradient of the norm square metric function, we present an
inexact MBFGS method with line search for solving symmetric nonlinear equations, which is …

The conjugate gradient projection method is one of the most effective methods for solving
large‐scale monotone nonlinear equations with convex constraints. In this paper, a new …

This article presents an inexact optimal hybrid conjugate gradient (CG) method for solving
symmetric nonlinear systems. The method is a convex combination of the optimal Dai–Liao …

In this paper, a new descent approximate modified residual algorithm is developed to solve
a large scale system of nonlinear symmetric equations, where the basic strategy to improve …

In this paper, we propose a norm descent derivative-free algorithm for solving large-scale
nonlinear symmetric equations without involving any information of the gradient or Jacobian …

In this article, we present a conjugate gradient method for large‐scale nonlinear equations
with symmetric Jacobian. The method is a modification of the descent Dai‐Liao conjugate …

Nonlinear conjugate gradient method is a popular approach for solving large-scale
unconstrained optimization problems due to its simplest iterative form and low storage …

In this paper, we consider a system of large-scale nonlinear monotone equations and
propose a class of derivative-free spectral conjugate gradient methods to solve it efficiently …

In this paper, we develop two algorithms to solve a nonlinear system of symmetric equations.
The first is an algorithm based on modifying two Broyden–Fletcher–Goldfarb–Shanno …