An interior Newton method for quadratic programming
type: Item
instance of: scholarly article
title: An interior Newton method for quadratic programming
zbMATH Open document ID: 0980.90099
author: Thomas F. Coleman
author: Jianguo Liu
published in: Mathematical Programming. Series A. Series B
publication date: 2000-11-12T00:00:00Z
full work available at URL: https://hdl.handle.net/1813/6166
review text: The authors propose a new (interior) approach for the general quadratic programming problem. They establish that the new method has strong convergence properties: The generated sequence converges globally to a point satisfying the second-order necessary optimility conditions, and the rate of convergence is 2-step quadratic if the limit point is a strong local minimizer. Published alternative interior approaches do not share such strong convergence properties for the nonconvex case. The authors also report on the results of preliminary numerical experiments: the results indicate that the proposed method has considerable practical potential.
reviewed by: Paulo Mbunga
Mathematics Subject Classification ID: 90C51
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 90C20
zbMATH DE Number: 1528057
zbMATH Keywords: nonconvex quadratic programming
zbMATH Keywords: interior method
zbMATH Keywords: Newton method
zbMATH Keywords: trust-region method
zbMATH Keywords: dogleg method
zbMATH Keywords: quadratic convergence
MaRDI profile type: Publication
OpenAlex ID: W2251458176
DOI: 10.1007/S101070050069
description: scientific article; zbMATH DE number 1528057