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Numerical Optimization (Springer Series in Operations Research and Financial Engineering) 🔍
Jorge Nocedal Stephen J. Wright Springer-Verlag GmbH, Springer Nature (Textbooks & Major Reference Works), New York, 2006
English [en] · PDF · 5.9MB · 2006 · 📘 Book (non-fiction) · 🚀/lgli/lgrs · Save
description
Numerical Optimization 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 the methods that are best suited to practical problems. For this new edition the book has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and 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. It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business. It also serves as a handbook for researchers and practitioners in the field. The authors have strived to produce a text that is pleasant to read, informative, and rigorous - one that reveals both the beautiful nature of the discipline and its practical side. There is a selected solutions manual for instructors for the new edition.
Alternative filename
lgrsnf/NumericalOptimization.pdf
Alternative author
Jorge Nocedal, Stephen Wright, Stephen Wright
Alternative author
Nocedal, Jorge, Wright, Stephen
Alternative publisher
Copernicus
Alternative publisher
Telos
Alternative edition
Springer series in operations research and financial engineering, 2. ed, New York, NY, 2006
Alternative edition
Springer series in operations research, 2nd ed, New York, ©2006
Alternative edition
United States, United States of America
Alternative edition
July 27, 2006
Alternative edition
2nd, PS, 2006
Alternative description
<p><P>Numerical Optimization 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 the methods that are best suited to practical problems.<p>For this new edition the book has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and 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. It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business. It also serves as a handbook for researchers and practitioners in the field. The authors have strived to produce a text that is pleasant to read, informative, and rigorous - one that reveals both the beautiful nature of the discipline and its practical side.<p>There is a selected solutions manual for instructors for the new edition.</p>
Alternative description
Title
Contents
Preface
Preface to the Second Edition
01 Introduction
02 Fundamentals of Unconstrained Optimization
03 Line Search Methods
04 Trust-Region Methods
05 Conjugate Gradient Methods
06 Quasi-Newton Methods
07 Large-Scale Unconstrained Optimization
08 Calculating Derivatives
09 Derivative-Free Optimization
10 Least-Squares Problems
11 Nonlinear Equations
12 Theory of Constrained Optimization
13 Linear Programming: The Simplex Method
14 Linear Programming: Interior-Point Methods
15 Fundamentals of Algorithms for Nonlinear Constrained Optimization
16 Quadratic Programming
17 Penalty and Augmented Lagrangian Methods
18 Sequential Quadratic Programming
19 Interior-Point Methods for Nonlinear Programming
Appendix A. Background Material
Appendix B. A Regularization Procedure
References
Index
Alternative description
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.
Alternative description
'Numerical Optimization' presents a comprehensive description of the effective methods in continuous optimization. The book includes chapters on nonlinear interior methods & derivative-free methods for optimization. It is useful for graduate students, researchers and practitioners
date open sourced
2024-10-06
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