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Numerical Optimization (Springer Series in Operations Research)

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Numerical Optimization (Springer Series in Operations Research) Cover

 

Synopses & Reviews

Publisher Comments:

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.Drawing on their experiences in teaching, research, and consulting, the authors have produced a textbook that will be of interest to students and practitioners alike. Each chapter begins with the basic concepts and builds up gradually to the best techniques currently available.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.Above all, 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.MMOR Mathematical Methods of Operations Research, 2001: "The book 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."

Synopsis:

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.

Description:

Includes bibliographical references (p. [611]-623) and index.

Table of Contents

Preface
x 1 Introduction
x 2 Fundamentals of Unconstrained Optimization
x 3 Line Search Methods
x 4 Trust-Region Methods
x 5 Conjugate Gradient Methods
x Practical Newton Methods
x 7 Calculating Derivatives
x 8 Quasi-Newton Methods
x 9 Large Scale Quasi-Newton and Partially Separable Optimization
x 10 Nonlinear Least-Square Problems
x 11 Nonlinear Equations
x 12 Theory of Constrained Optimization
x 13 Linear Programming: The Simplex Method
x 14 Linear Programming: Interior-Point Methods
x 15 Fundamentals of Algorithms for Nonlinear Constrained Optimization
x 16 Quadratic Programming
x 17 Penalty, Barrier, and Augmented Lagrangian Algorithms
x 18 Sequential Quadratic Programming
x Appendix: Background Material
x Bibliography
x Index

Product Details

ISBN:
9780387987934
Author:
Nocedal, Jorge
Author:
Wright, Stephen J.
Publisher:
Springer
Location:
New York :
Subject:
Linear Programming
Subject:
Game Theory
Subject:
Mathematical optimization
Copyright:
Edition Number:
1
Edition Description:
1999. Corr. 2nd
Series:
Springer Series in Operations Research and Financial Engineering
Series Volume:
no. 1862
Publication Date:
April 2000
Binding:
Hardcover
Language:
English
Illustrations:
Y
Pages:
636
Dimensions:
9.48x7.31x1.46 in. 2.74 lbs.

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Related Subjects

Science and Mathematics » Biology » General
Science and Mathematics » Mathematics » Advanced

Numerical Optimization (Springer Series in Operations Research) Used Hardcover
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Product details 636 pages Springer-Verlag - English 9780387987934 Reviews:
"Synopsis" by , 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.
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