Jonathan Borwein & Adrian S. Lewis 
Convex Analysis and Nonlinear Optimization 
Theory and Examples

Optimization is a rich and thriving mathematical discipline, and the underlying theory of current computational optimization techniques grows ever more sophisticated. This book aims to provide a concise, accessible account of convex analysis and its applications and extensions, for a broad audience. Each section concludes with an often extensive set of optional exercises. This new edition adds material on semismooth optimization, as well as several new proofs.

Table des matières

Background.- Inequality constraints.- Fenchel duality.- Convex analysis.- Special cases.- Nonsmooth optimization.- The Karush-Kuhn-Tucker Theorem.- Fixed points.- Postscript: infinite versus finite dimensions.- List of results and notation.