New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization

Publication date: 4 June 2009

Published in: Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: http://www.scielo.br/scielo.php?script=sci_abstract&pid=S1807-03022009000100006&lng=en&nrm=iso&tlng=en

zbMATH Keywords

global convergence numerical results quasi-Newton methods descent methods descent direction Polak-Ribière-Polyak method Hestenes-Stiefel nonlinear conjugate gradient method HS method inexact line searches

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Methods of quasi-Newton type (90C53)

Related Items (6)

A descent Dai-Liao conjugate gradient method based on a modified secant equation and its global convergence ⋮ Conjugate gradient methods based on secant conditions that generate descent search directions for unconstrained optimization ⋮ A modified Hestense–Stiefel conjugate gradient method close to the memoryless BFGS quasi-Newton method ⋮ Some sufficient descent conjugate gradient methods and their global convergence ⋮ A three term Polak-Ribière-Polyak conjugate gradient method close to the memoryless BFGS quasi-Newton method ⋮ An Efficient Hybrid Conjugate Gradient Method for Unconstrained Optimisation

Uses Software

SCALCG

This page was built for publication: New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization