Two general methods for computing saddle points with applications for decomposing convex programming problems
type: Item
instance of: scholarly article
title: Two general methods for computing saddle points with applications for decomposing convex programming problems
zbMATH Open document ID: 0584.65035
DOI: 10.1007/BF01442200
published in: Applied Mathematics and Optimization
publication date: 1985-01-01T00:00:00Z
review text: Two new methods are presented for computing saddle points in finite- dimensional spaces. One of the methods is a modification of the column method given by Dantzig and Wolfe, obtained by regularizing the Lagrangian. The other method is a symmetric modification of the above. The principal application of the methods presented here is to give new decomposition algorithms for solving separable convex programming problems.
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 90C25
zbMATH DE Number: 3936394
zbMATH Keywords: saddle points
zbMATH Keywords: column method
zbMATH Keywords: decomposition algorithms
zbMATH Keywords: separable convex programming
author: A. Auslender
MaRDI profile type: Publication
cites work: Q3844775
cites work: Numerical methods for finding saddle points
cites work: Coincidence properties of birth and death processes
cites work: Convex Analysis
cites work: Q4050397
cites work: Applications of the method of partial inverses to convex programming: Decomposition
cites work: Q5589748
full work available at URL: https://doi.org/10.1007/bf01442200
OpenAlex ID: W1991689826
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description: scientific article; zbMATH DE number 3936394