Augmented penalty algorithms based on BFGS secant approximations and trust regions
type: Item
instance of: scholarly article
title: Augmented penalty algorithms based on BFGS secant approximations and trust regions
zbMATH Open document ID: 1113.65061
author: G. M. Croceri
author: G. N. Sottosanto
author: María Cristina Maciel
published in: Applied Numerical Mathematics
publication date: 2007-03-12T00:00:00Z
review text: The authors study an iterative method for solving general nonlinear, equality-constrained optimization problem, based on a series of consecutive optimizations of the augmented Lagrangian function. They begin by a section where the basic definitions and introductory theorems are outlined. This is followed by section~2 which contains a description of the main algorithm which consists of an augmented Lagrangian scheme. Several elements of the proposed algorithm are presented and described in a lot of details, including the updating of the penalty function and the Hessian, the inner and outer iteration algorithms and the termination criteria. The article concludes with an indicative example, a section containing the results of numerical experimentation and a list of relevant references.
reviewed by: Efstratios Rappos
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 90C51
zbMATH DE Number: 5133018
zbMATH Keywords: augmented Lagrangian algorithm
zbMATH Keywords: secant methods
zbMATH Keywords: nonlinear least squares
zbMATH Keywords: numerical examples
zbMATH Keywords: trust region method
zbMATH Keywords: Broyden-Fletcher-Goldfarb-Shanno (BFGS) method
describes a project that uses: NL2SOL
MaRDI profile type: Publication
full work available at URL: j.apnum.2006.04.001
OpenAlex ID: W2086126844
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DOI: 10.1016/J.APNUM.2006.04.001
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description: scientific article; zbMATH DE number 5133018