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 ...

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 ...

In this paper, three new hybrid nonlinear conjugate gradient methods are presented, which produce suf?cient descent search direction at every iteration. This property is independent of any line search ...

Abstract: This thesis further study descent conjugate gradient methods based on the modified FR method and the modified PRP method give the class of conjugate gradient methods formed by the convex ...

This is a preview. Log in through your library . Abstract In this paper, we focus on the stochastic inverse eigenvalue problem of reconstructing a stochastic matrix from the prescribed spectrum. We ...

In this paper we test different conjugate gradient (CG) methods for solving largescale unconstrained optimization problems. The methods are divided in two groups: the first group includes five basic ...

The Fletcher-Reeves conjugate gradient ( FR ) method is the earliest nonlinear conjugate gradient method. It was obtained by Fletcher and Reeves in 1964 by extending the conjugate gradient method for ...