Numerical Optimization
Published on 28. April 2000
Book
Hardback
XXI, 636 pages
978-0-387-98793-4 (ISBN)
Description
The new edition of this book presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on methods best suited to practical problems. This edition has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are widely used in practice and are the focus of much current research. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience.
More details
Series
Edition
1st. ed. 1999. Corr. 2nd printing
Language
English
Place of publication
NY
United States
Target group
College/higher education
Professional and scholarly
Illustrations
8
8 s/w Tabellen
85 illus.
Dimensions
Height: 23.5 cm
Width: 17.8 cm
Weight
1240 gr
ISBN-13
978-0-387-98793-4 (9780387987934)
DOI
10.1007/b98874
Schweitzer Classification
Other editions
New editions
Jorge Nocedal | Stephen Wright
Numerical Optimization
Book
07/2006
2nd Edition
Springer
€74.89
Available immediately
Additional editions
Jorge Nocedal | Stephen Wright
Numerical Optimization
E-Book
06/2006
1st Edition
Springer
€85.59
Available for download
Content
Preface.-Preface to the Second Edition.-Introduction.-Fundamentals of Unconstrained Optimization.-Line Search Methods.-Trust-Region Methods.-Conjugate Gradient Methods.-Quasi-Newton Methods.-Large-Scale Unconstrained Optimization.-Calculating Derivatives.-Derivative-Free Optimization.-Least-Squares Problems.-Nonlinear Equations.-Theory of Constrained Optimization.-Linear Programming: The Simplex Method.-Linear Programming: Interior-Point Methods.-Fundamentals of Algorithms for Nonlinear Constrained Optimization.-Quadratic Programming.-Penalty and Augmented Lagrangian Methods.-Sequential Quadratic Programming.-Interior-Point Methods for Nonlinear Programming.-Background Material.- Regularization Procedure.