Numerical Optimization / Edition 2

by Jorge Nocedal, Stephen Wright

Overview

The new edition of this book presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It is enhanced by new chapters on nonlinear interior methods and derivative-free methods for optimization.

Product Details

ISBN-13:	9780387303031
Publisher:	Springer New York
Publication date:	07/27/2006
Series:	Springer Series in Operations Research and Financial Engineering
Edition description:	2nd ed. 2006
Pages:	664
Product dimensions:	7.01(w) x 9.25(h) x 0.06(d)

Table of Contents

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.

Editorial Reviews

MMOR Mathematical Methods of Operations Research, 2001: "The books looks very suitable to be used in an graduate-level course in optimization for students in mathematics, operations research, engineering, and others. Moreover, it seems to be very helpful to do some self-studies in optimization, to complete own knowledge and can be a source of new ideas.... I recommend this excellent book to everyone who is interested in optimization problems."

From the Publisher