Separation approach for augmented lagrangians in Constrained nonconvex optimization
type: Item
instance of: scholarly article
title: Separation approach for augmented lagrangians in Constrained nonconvex optimization
zbMATH Open document ID: 1190.90143
author: B. E. Eshmatov
published in: Journal of Optimization Theory and Applications
publication date: 2010-04-13T00:00:00Z
review text: The authors consider a finite-dimensional inequality-constrained optimization problem. Main results of the image space analysis are recalled (see \textit{F. Gianessi} [Constraint optimization and image space analysis, Springer Verlag, Berlin (2005)]). By means of this theory, local and global saddle point conditions for a general class of augmented Lagrangian functions under suitable conditions are proved. The existence of the global saddle-point does not require the compactness of the feasible set.
reviewed by: Karel Zimmermann
Mathematics Subject Classification ID: 90C26
Mathematics Subject Classification ID: 90C30
zbMATH DE Number: 5692385
zbMATH Keywords: image space analysis
zbMATH Keywords: separation
zbMATH Keywords: saddle points
zbMATH Keywords: augmented Lagrangian function
MaRDI profile type: Publication
full work available at URL: s10957-009-9598-0
OpenAlex ID: W2088807200
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DOI: 10.1007/S10957-009-9598-0
description: scientific article; zbMATH DE number 5692385