Numerical Optimization

Front Cover
Springer Science & Business Media, Dec 11, 2006 - Mathematics - 664 pages

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.


 

Contents

CHAPTER 1 Introduction
1
CHAPTER 2 Fundamentals of Unconstrained Optimization
10
CHAPTER 3 Line Search Methods
30
CHAPTER 4 TrustRegion Methods
66
CHAPTER 5 Conjugate Gradient Methods
101
CHAPTER 6 QuasiNewton Methods
135
CHAPTER 7 LargeScale Unconstrained Optimization
164
CHAPTER 8 Calculating Derivatives
193
The Simplex Method
355
InteriorPoint Methods
392
CHAPTER 15 Fundamentals of Algorithms for Nonlinear Constrained Optimization
421
CHAPTER 16 Quadratic Programming
448
CHAPTER 17 Penalty and Augmented Lagrangian Methods
497
CHAPTER 18 Sequential Quadratic Programming
529
CHAPTER 19 InteriorPoint Methodsfor Nonlinear Programming
563
APPENDIX A Background Material
598

CHAPTER 9 DerivativeFree Optimization
220
CHAPTER 10 LeastSquares Problems
245
CHAPTER 11 Nonlinear Equations
270
CHAPTER 12 Theory of Constrained Optimization
304
APPENDIX B A Regularization Procedure
635
References
637
Index
653
Copyright

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