# An Introduction to Optimization, 4 edition

EPUB

- eBook:An Introduction to Optimization, 4 edition
- Author:Edwin K. P. Chong, Stanislaw H. Zak
- Edition:4 edition
- Categories:
- Data:2013-01-14
- ISBN:1118279018
- ISBN-13:9781118279014
- Language:English
- Pages:640
- Format:EPUB

**Book Description**

## An Introduction to Optimization, 4 edition *by Edwin K. P. Chong, Stanislaw H. Zak*

*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.

**Content**

Chapter 1: Methods of Proof and Some Notation

Chapter 2: Vector Spaces and Matrices

Chapter 3: Transformations

Chapter 4: Concepts from Geometry

Chapter 5: Elements of Calculus

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

Chapter 16: Simplex Method

Chapter 17: Duality

Chapter 18: Nonsimplex Methods

Chapter 19: Integer Linear Programming

Part IV: Nonlinear Constrained Optimization

Chapter 20: Problems with Equality Constraints

Chapter 21: Problems with Inequality Constraints

Chapter 22: Convex Optimization Problems

Chapter 23: Algorithms for Constrained Optimization

Chapter 24: Multiobjective Optimization

Download