The global convergence of augmented Lagrangian methods based on NCP function in constrained nonconvex optimization
type: Item
instance of: scholarly article
title: The global convergence of augmented Lagrangian methods based on NCP function in constrained nonconvex optimization
zbMATH Open document ID: 1160.65031
author: J. Martínez
published in: Applied Mathematics and Computation
publication date: 2009-03-02T00:00:00Z
review text: The authors study the global convergence properties for modified augmented Lagrangian methods using a class of augmented Lagrangian functions based on nonlinear complementarity problem (NCP) function for inequality constrained optimization problems. They show that under weaker conditions, the augmented Lagrangian method using safeguarding strategy converges to a Karush-Kuhn-Tucker point or a degenerate point of the original problem. The convergence properties of the augmented Lagrangian method using conditional multiplier updating rule is presented. The use of penalty parameter updating criteria and normalization of the multipliers in augmented Lagrangian methods is investigated. Some preliminary numerical results on the four proposed modified augmented algorithms are presented.
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 90C26
Mathematics Subject Classification ID: 90C33
zbMATH DE Number: 5522196
zbMATH Keywords: nonconvex optimization
zbMATH Keywords: constrained optimization
zbMATH Keywords: augmented Lagrangian methods
zbMATH Keywords: convergence to KKT point
zbMATH Keywords: degenerate point
zbMATH Keywords: nonlinear complementarity problem
zbMATH Keywords: Karush-Kuhn-Tucker point
zbMATH Keywords: numerical results
zbMATH Keywords: algorithms
MaRDI profile type: Publication
full work available at URL: j.amc.2008.10.015
OpenAlex ID: W2026116392
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DOI: 10.1016/J.AMC.2008.10.015
description: scientific article; zbMATH DE number 5522196