Optimization 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.