Conjugate Gradient (CG) method was initially proposed for solving linear systems and
unconstrained minimization. The method is an excellent choice for solving optimization …

In our research, a new conjugate gradient (CG) method for solving nonlinear systems of
equations is introduced and studied. The proposed method defined as a convex …

Many researchers are interested for developed and improved the conjugate gradient
method for solving large scale unconstrained optimization problems. In this work a new …

Optimization problem is a type of mathematical problem with several uses in real life. As one
of the commonly applied methods for solving optimization problem, the conjugate gradient …

Optimization is now considered a branch of computational science. This ethos seeks to
answer the question «what is best?» by looking at problems where the quality of any answer …

This paper considers the acceleration of the gradient algorithm for the linear models.
Traditional stochastic gradient algorithm requires less computation, but it converges to the …

In this study, we propose a new modified hybrid conjugate gradient projection method with a
new scale parameter φk for solving large‐scale nonlinear monotone equations. The …

This article presents a new conjugate gradient (CG) method that requires first-order
derivatives but overcomes the slow convergence issue associated with the steepest descent …

In this paper, we have investigated a new spectral Quasi-Newton (QN) algorithm. New
search directions of the proposed algorithm increase its stability and increase the arrival to …

Conjugate gradient (CG) method is one of the method among researchers in solving
optimization problem. It possesses characteristics that put it in between steepest descent …