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Duality for Nonconvex Approximation and Optimization

(Autor)

Buch | Hardcover
356 Seiten
2006 | 2006 ed.
Springer-Verlag New York Inc.
978-0-387-28394-4 (ISBN)

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Duality for Nonconvex Approximation and Optimization - Ivan Singer
CHF 149,75 inkl. MwSt
Researchers have been studying complicated classes of problems that can be studied by means of convex analysis, so-called "anticonvex" and "convex-anticonvex" optimization problems. This monograph contains a presentation of the duality theory for these classes of problems and their generalizations.
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.

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.

Reihe/Serie CMS Books in Mathematics
Zusatzinfo 17 Illustrations, black and white; XX, 356 p. 17 illus.
Verlagsort New York, NY
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Mathematik Analysis
Mathematik / Informatik Mathematik Angewandte Mathematik
Mathematik / Informatik Mathematik Finanz- / Wirtschaftsmathematik
ISBN-10 0-387-28394-3 / 0387283943
ISBN-13 978-0-387-28394-4 / 9780387283944
Zustand Neuware
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