Duality for Nonconvex Approximation and Optimization

Ivan Singer - Collection CMS Books in Mathematics

370 pages, parution le 25/04/2005

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Résumé

The theory of convex optimization has been constantly developing over the past 30 years. Most recently, many researchers have been studying more complicated classes of problems that still can be studied by means of convex analysis, so-called "anticonvex" and "convex-anticonvex" optimizaton problems. This manuscript contains an exhaustive presentation of the duality for these classes of problems and some of its generalization in the framework of abstract convexity. This manuscript will be of great interest for experts in this and related fields.

Written for: Research mathematicians, graduate students

Sommaire

Preliminaries
Worst Approximation
Duality for Quasi-convex Supremization
Optimal Solutions for Quasi-convex Maximization
Reverse Convex Best Approximation
Unperturbational Duality for Reverse Convex Infimization
Optimal Solutions for Reverse Convex Infimization
Duality for D.C. Optimization Problems
Duality for Optimization in the Framework of Abstract Convexity
Notes and Remarks

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Ivan Singer
Collection	CMS Books in Mathematics
Parution	25/04/2005
Nb. de pages	370
Format	16 x 24
Couverture	Relié
Poids	645g
Intérieur	Noir et Blanc
EAN13	9780387283944
ISBN13	978-0-387-28394-4