Numerical Optimization PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Numerical Optimization PDF full book. Access full book title Numerical Optimization.

Numerical Optimization

Numerical Optimization
Author: Jorge Nocedal
Publisher: Springer Science & Business Media
Total Pages: 686
Release: 2006-12-11
Genre: Mathematics
ISBN: 0387400656

Download Numerical Optimization Book in PDF, ePub and Kindle

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.


Numerical Optimization

Numerical Optimization
Author: Jorge Nocedal
Publisher: Springer Science & Business Media
Total Pages: 651
Release: 2006-06-06
Genre: Mathematics
ISBN: 0387227423

Download Numerical Optimization Book in PDF, ePub and Kindle

The new edition of this book 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 methods best suited to practical problems. This edition has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are widely used in practice and are 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.


Numerical Optimization

Numerical Optimization
Author: Joseph-Frédéric Bonnans
Publisher: Springer Science & Business Media
Total Pages: 421
Release: 2013-03-14
Genre: Mathematics
ISBN: 3662050781

Download Numerical Optimization Book in PDF, ePub and Kindle

This book starts with illustrations of the ubiquitous character of optimization, and describes numerical algorithms in a tutorial way. It covers fundamental algorithms as well as more specialized and advanced topics for unconstrained and constrained problems. This new edition contains computational exercises in the form of case studies which help understanding optimization methods beyond their theoretical description when coming to actual implementation.


Mathematical Theory of Optimization

Mathematical Theory of Optimization
Author: Ding-Zhu Du
Publisher: Springer Science & Business Media
Total Pages: 277
Release: 2013-03-14
Genre: Mathematics
ISBN: 1475757956

Download Mathematical Theory of Optimization Book in PDF, ePub and Kindle

This book provides an introduction to the mathematical theory of optimization. It emphasizes the convergence theory of nonlinear optimization algorithms and applications of nonlinear optimization to combinatorial optimization. Mathematical Theory of Optimization includes recent developments in global convergence, the Powell conjecture, semidefinite programming, and relaxation techniques for designs of approximation solutions of combinatorial optimization problems.


Numerical PDE-Constrained Optimization

Numerical PDE-Constrained Optimization
Author: Juan Carlos De los Reyes
Publisher: Springer
Total Pages: 123
Release: 2015-02-06
Genre: Mathematics
ISBN: 3319133950

Download Numerical PDE-Constrained Optimization Book in PDF, ePub and Kindle

This book introduces, in an accessible way, the basic elements of Numerical PDE-Constrained Optimization, from the derivation of optimality conditions to the design of solution algorithms. Numerical optimization methods in function-spaces and their application to PDE-constrained problems are carefully presented. The developed results are illustrated with several examples, including linear and nonlinear ones. In addition, MATLAB codes, for representative problems, are included. Furthermore, recent results in the emerging field of nonsmooth numerical PDE constrained optimization are also covered. The book provides an overview on the derivation of optimality conditions and on some solution algorithms for problems involving bound constraints, state-constraints, sparse cost functionals and variational inequality constraints.


Numerical Methods and Optimization in Finance

Numerical Methods and Optimization in Finance
Author: Manfred Gilli
Publisher: Academic Press
Total Pages: 638
Release: 2019-08-30
Genre:
ISBN: 0128150653

Download Numerical Methods and Optimization in Finance Book in PDF, ePub and Kindle

Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems-ranging from asset allocation to risk management and from option pricing to model calibration-can be efficiently handled using modern computational techniques. Numerical Methods and Optimization in Finance presents such computational techniques, with an emphasis on simulation and optimization, particularly so-called heuristics. This book treats quantitative analysis as an essentially computational discipline in which applications are put into software form and tested empirically. This revised edition includes two new chapters, a self-contained tutorial on implementing and using heuristics, and an explanation of software used for testing portfolio-selection models. Postgraduate students, researchers in programs on quantitative and computational finance, and practitioners in banks and other financial companies can benefit from this second edition of Numerical Methods and Optimization in Finance. Introduces numerical methods to readers with economics backgrounds Emphasizes core simulation and optimization problems Includes MATLAB and R code for all applications, with sample code in the text and freely available for download


Iterative Methods for Optimization

Iterative Methods for Optimization
Author: C. T. Kelley
Publisher: SIAM
Total Pages: 195
Release: 1999-01-01
Genre: Mathematics
ISBN: 9781611970920

Download Iterative Methods for Optimization Book in PDF, ePub and Kindle

This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley's book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference. Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke-Jeeves, implicit filtering, MDS, and Nelder-Mead schemes in a unified way, and also the first book to make connections between sampling methods and the traditional gradient-methods. Each of the main algorithms in the text is described in pseudocode, and a collection of MATLAB codes is available. Thus, readers can experiment with the algorithms in an easy way as well as implement them in other languages.


Numerical Methods for Unconstrained Optimization and Nonlinear Equations

Numerical Methods for Unconstrained Optimization and Nonlinear Equations
Author: J. E. Dennis, Jr.
Publisher: SIAM
Total Pages: 394
Release: 1996-12-01
Genre: Mathematics
ISBN: 9781611971200

Download Numerical Methods for Unconstrained Optimization and Nonlinear Equations Book in PDF, ePub and Kindle

This book has become the standard for a complete, state-of-the-art description of the methods for unconstrained optimization and systems of nonlinear equations. Originally published in 1983, it provides information needed to understand both the theory and the practice of these methods and provides pseudocode for the problems. The algorithms covered are all based on Newton's method or "quasi-Newton" methods, and the heart of the book is the material on computational methods for multidimensional unconstrained optimization and nonlinear equation problems. The republication of this book by SIAM is driven by a continuing demand for specific and sound advice on how to solve real problems. The level of presentation is consistent throughout, with a good mix of examples and theory, making it a valuable text at both the graduate and undergraduate level. It has been praised as excellent for courses with approximately the same name as the book title and would also be useful as a supplemental text for a nonlinear programming or a numerical analysis course. Many exercises are provided to illustrate and develop the ideas in the text. A large appendix provides a mechanism for class projects and a reference for readers who want the details of the algorithms. Practitioners may use this book for self-study and reference. For complete understanding, readers should have a background in calculus and linear algebra. The book does contain background material in multivariable calculus and numerical linear algebra.


Matrix, Numerical, and Optimization Methods in Science and Engineering

Matrix, Numerical, and Optimization Methods in Science and Engineering
Author: Kevin W. Cassel
Publisher: Cambridge University Press
Total Pages: 728
Release: 2021-03-04
Genre: Technology & Engineering
ISBN: 1108787622

Download Matrix, Numerical, and Optimization Methods in Science and Engineering Book in PDF, ePub and Kindle

Address vector and matrix methods necessary in numerical methods and optimization of linear systems in engineering with this unified text. Treats the mathematical models that describe and predict the evolution of our processes and systems, and the numerical methods required to obtain approximate solutions. Explores the dynamical systems theory used to describe and characterize system behaviour, alongside the techniques used to optimize their performance. Integrates and unifies matrix and eigenfunction methods with their applications in numerical and optimization methods. Consolidating, generalizing, and unifying these topics into a single coherent subject, this practical resource is suitable for advanced undergraduate students and graduate students in engineering, physical sciences, and applied mathematics.