The nonlinear conjugate gradient method is a very useful technique for solving large scale minimization problems and has wide applications in many fields. In this paper, we present a new algorithm of ...

Abstract: Conjugate gradient techniques are widely used to solve unconstrained optimization issues. The accelerated conjugate gradient approach provides superior numerical effects for the ...

Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...

Abstract: This paper presents a new three-term hybrid conjugate gradient projection method for handling large-scale convex-constrained nonlinear monotone equations that are prevalent in fields such as ...

Such systems arise widely in applied mathematics, particularly in the numerical solution of partial differential equations (PDEs), optimisation problems, and data-driven applications. While direct ...

ABSTRACT: Three PRP-type direct search methods for unconstrained optimization are presented. The methods adopt three kinds of recently developed descent conjugate gradient methods and the idea of ...

The Conjugate Gradient Method is the most prominent iterative method for solving sparse systems of linear equations. Unfortunately, many textbook treatments of the topic are written with neither ...