Ivan Singer 
Duality for Nonconvex Approximation and Optimization 

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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.
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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.
Idioma Inglés ● Formato PDF ● Páginas 356 ● ISBN 9780387283951 ● Tamaño de archivo 14.6 MB ● Edad 02-99 años ● Editorial Springer New York ● Ciudad NY ● País US ● Publicado 2007 ● Descargable 24 meses ● Divisa EUR ● ID 2144473 ● Protección de copia Adobe DRM
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