Numerical Optimization / Edition 2

Numerical Optimization / Edition 2

3.0 2
by Jorge Nocedal, Stephen Wright
     
 

ISBN-10: 0387303030

ISBN-13: 9780387303031

Pub. Date: 09/15/2009

Publisher: Springer New York

Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very…  See more details below

Overview

Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

Product Details

ISBN-13:
9780387303031
Publisher:
Springer New York
Publication date:
09/15/2009
Series:
Springer Series in Operations Research and Financial Engineering
Edition description:
2nd ed. 2006
Pages:
664
Sales rank:
485,913
Product dimensions:
7.01(w) x 9.25(h) x 0.06(d)

Table of Contents

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.

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Numerical Optimization 5 out of 5 based on 0 ratings. 1 reviews.
satchel1979 More than 1 year ago
This book presents very clear pictures of fundamental theory and algorithms in numerical optimization. I especially like the way that it universally put Newton, Quazi-Newton, Conjugate Gradient methods into single framework and explains them in a very intuitive-friend way. To those who want to learn numerical optimization, I can only say: Read the Book.