Convex Analysis and Nonlinear Optimization: Theory and ExamplesOptimization is a rich and thriving mathematical discipline. The theory underlying current computational optimization techniques grows ever more sophisticated. The powerful and elegant language of convex analysis unifies much of this theory. The aim of this book is to provide a concise, accessible account of convex analysis and its applications and extensions, for a broad audience. It can serve as a teaching text, at roughly the level of first year graduate students. While the main body of the text is self-contained, each section concludes with an often extensive set of optional exercises. The new edition adds material on semismooth optimization, as well as several new proofs that will make this book even more self-contained. |
From inside the book
... linear Models and Taking Advantage of Non - Negativity Constraints to Find the Optimal Solution for Some Neutrosophic linear Models in Which the Number of Unknowns is More than Three * 1Maissam Jdid , 2Florentin Smarandache ' Faculty ...
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Or the Scenographic Projections of Descriptive Geometry Samuel Edward Warren. i 1 1 6572 GENERAL PROBLEMS LINEAR IN THE PERSPECTIVE OF.
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... linear drawing side by side with that of free - hand ; and to bring linear drawing within the reach of the young is the main object of this book . In composing it , I have endeavoured to render it a simple progressive and pleasant ...
Contents
Chapter 1 Background | 1 |
Chapter 2 Inequality Constraints | 15 |
Chapter 3 Fenchel Duality | 33 |
Chapter 4 Convex Analysis | 65 |
Chapter 5 Special Cases | 97 |
Chapter 6 Nonsmooth Optimization | 123 |
Chapter 7 KarushKuhnTucker Theory | 153 |