Convex Analysis and Nonlinear Optimization

Theory and Examples
Softcover Nachdruck of hardcover 2. Auflage 2006
ISBN: 978-1-4419-2127-7
Verlag: Springer

Buch, Englisch, 310 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 493 g

Reihe: CMS Books in Mathematics

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.

Zielgruppe

Graduate

Autoren/Hrsg.

Lewis, Adrian S.

Borwein, Jonathan

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
• Mathematik | Informatik Mathematik Mathematische Analysis Funktionentheorie, Komplexe Analysis

Inhaltsverzeichnis

Background.- Inequality Constraints.- Fenchel Duality.- Convex Analysis.- Special Cases.- Nonsmooth Optimization.- Karush—Kuhn—Tucker Theory.- Fixed Points.- More Nonsmooth Structure.- Postscript: Infinite Versus Finite Dimensions.- List of Results and Notation.

Über Autor(innen)

Jonathan M. Borwein, FRSC is Canada Research Chair in Collaborative Technology at Dalhousie University. A Fellow of the AAAS and a foreign member of the Bulgarian Academy of Science, he received his Doctorate from Oxford in 1974 as a Rhodes Scholar and has worked at Waterloo, Carnegie Mellon and Simon Fraser Universities. Recognition for his extensive publications in optimization, analysis and computational mathematics includes the 1993 Chauvenet prize.

Adrian S. Lewis is a Professor in the School of Operations Research and Industrial Engineering at Cornell. Following his 1987 Doctorate from Cambridge, he has worked at Waterloo and Simon Fraser Universities. He received the 1995 Aisenstadt Prize, from the University of Montreal, and the 2003 Lagrange Prize for Continuous Optimization, from SIAM and the Mathematical Programming Society.