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Practical Optimization: Algorithms and Engineering Applications
Practical Optimization: Algorithms and Engineering Applications
Date: 06 May 2011, 20:24

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Practical Optimization: Algorithms and Engineering Applications provides a hands-on treatment of the subject of optimization. A comprehensive set of problems and exercises makes the book suitable for use in one or two semesters of a first-year graduate course or an advanced undergraduate course. Each half of the book contains a full semesters worth of complimentary yet stand-alone material. The practical orientation of the topics chosen and a wealth of useful examples also make the book suitable as a reference work for practitioners in the field.
Advancements in the efficiency of digital computers and the evolution of reliable software for numerical computation during the past three decades have led to a rapid growth in the theory, methods, and algorithms of numerical optimization. This body of knowledge has motivated widespread applications of optimization methods in many disciplines, e.g., engineering, business, and science, and has subsequently led to problem solutions that were considered intractable not too long ago.
Key Features:
* extensively class-tested
* provides a complete teaching package with MATLAB exercises and online solutions to end-of-chapter problems
* includes recent methods of emerging interest such as semidefinite programming and second-order cone programming
* presents a unified treatment of unconstrained and constrained optimization
* uses a practical treatment of optimization accessible to broad audience, from college students to scientists and industry professionals
* provides a thorough appendix with background theory so non-experts can understand how applications are solved from point of view of optimization
CONTENTS
1. THE OPTIMIZATION PROBLEM
2. BASIC PRINCIPLES
3. GENERAL PROPERTIES OF ALGORITHMS
4. ONE-DIMENSIONAL OPTIMIZATION
5. BASIC MULTIDIMENSIONAL GRADIENT METHODS
6. CONJUGATE-DIRECTION METHODS
7. QUASI-NEWTON METHODS
8. MINIMAX METHODS
9. APPLICATIONS OF UNCONSTRAINED OPTIMIZATION
10. FUNDAMENTALS OF CONSTRAINED OPTIMIZATION
11. LINEAR PROGRAMMING PART I: THE SIMPLEX METHOD
12. LINEAR PROGRAMMING PART II: INTERIOR-POINT METHODS
13. QUADRATIC AND CONVEX PROGRAMMING
14. SEMIDEFINITE AND SECOND-ORDER CONE PROGRAMMING
15. GENERAL NONLINEAR OPTIMIZATION PROBLEMS
16. APPLICATIONS OF CONSTRAINED OPTIMIZATION
Appendices
A Basics of Linear Algebra
B Basics of Digital Filters
Index
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