Duality for Nonconvex Approximation and Optimization
(Sprache: Englisch)
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"...
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Klappentext zu „Duality for Nonconvex Approximation and Optimization “
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.
Inhaltsverzeichnis zu „Duality for Nonconvex Approximation and Optimization “
- 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.
Bibliographische Angaben
- Autor: Ivan Singer
- 2006, 356 Seiten, Maße: 15,9 x 24,5 cm, Gebunden, Englisch
- Verlag: Springer, New York
- ISBN-10: 0387283943
- ISBN-13: 9780387283944
Sprache:
Englisch
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