Book description
Praise for the Third Edition ". . . guides and leads the reader through the learning path . . . [e]xamples are stated very clearly and the results are presented with attention to detail." —MAA Reviews
Fully updated to reflect new developments in the field, the Fourth Edition of Introduction to Optimization fills the need for accessible treatment of optimization theory and methods with an emphasis on engineering design. Basic definitions and notations are provided in addition to the related fundamental background for linear algebra, geometry, and calculus.
This new edition explores the essential topics of unconstrained optimization problems, linear programming problems, and nonlinear constrained optimization. The authors also present an optimization perspective on global search methods and include discussions on genetic algorithms, particle swarm optimization, and the simulated annealing algorithm. Featuring an elementary introduction to artificial neural networks, convex optimization, and multi-objective optimization, the Fourth Edition also offers:
A new chapter on integer programming
Expanded coverage of one-dimensional methods
Updated and expanded sections on linear matrix inequalities
Numerous new exercises at the end of each chapter
MATLAB exercises and drill problems to reinforce the discussed theory and algorithms
Numerous diagrams and figures that complement the written presentation of key concepts
MATLAB M-files for implementation of the discussed theory and algorithms (available via the book's website)
Introduction to Optimization, Fourth Edition is an ideal textbook for courses on optimization theory and methods. In addition, the book is a useful reference for professionals in mathematics, operations research, electrical engineering, economics, statistics, and business.
Table of contents
- Cover
- Half Title page
- Title page
- Copyright page
- Dedication
- Preface
- Part I: Mathematical Review
-
Part II: Unconstrained Optimization
- Chapter 6: Basics of Set-Constrained and Unconstrained Optimization
- Chapter 7: One-Dimensional Search Methods
- Chapter 8: Gradient Methods
- Chapter 9: Newton’s Method
- Chapter 10: Conjugate Direction Methods
- Chapter 11: Quasi-Newton Methods
- Chapter 12: Solving Linear Equations
- Chapter 13: Unconstrained Optimization and Neural Networks
- Chapter 14: Global Search Algorithms
-
Part III: Linear Programming
-
Chapter 15: Introduction to Linear Programming
- 15.1 Brief History of Linear Programming
- 15.2 Simple Examples of Linear Programs
- 15.3 Two-Dimensional Linear Programs
- 15.4 Convex Polyhedra and Linear Programming
- 15.5 Standard Form Linear Programs
- 15.6 Basic Solutions
- 15.7 Properties of Basic Solutions
- 15.8 Geometric View of Linear Programs
- Exercises
- Chapter 16: Simplex Method
- Chapter 17: Duality
- Chapter 18: Nonsimplex Methods
- Chapter 19: Integer Linear Programming
-
Chapter 15: Introduction to Linear Programming
- Part IV: Nonlinear Constrained Optimization
- References
- Index
Product information
- Title: An Introduction to Optimization, 4th Edition
- Author(s):
- Release date: January 2013
- Publisher(s): Wiley
- ISBN: 9781118279014
You might also like
book
Designing Data-Intensive Applications, 2nd Edition
Data is at the center of many challenges in system design today. Difficult issues such as …
book
A Common-Sense Guide to Data Structures and Algorithms, Second Edition, 2nd Edition
Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write …
book
Learning Domain-Driven Design
Building software is harder than ever. As a developer, you not only have to chase ever-changing …
book
Designing Data-Intensive Applications
Data is at the center of many challenges in system design today. Difficult issues need to …