- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
The revised and updated new edition of the popular optimization book for engineers
The thoroughly revised and updated fifth edition ofĀ Engineering Optimization: Theory and PracticeĀ offers engineers a guide to the important optimization methods that are commonly used in a wide range of industries. The authorāa noted expert on the topicāpresents both the classical and most recent optimizations approaches. The book introduces the basic methods and includes information on more advanced principles and applications.
The fifth edition presents four new chapters: Solution of Optimization Problems Using MATLAB; Metaheuristic Optimization Methods; Multi-Objective Optimization Methods; and Practical Implementation of Optimization. All of the book's topics are designed to be self-contained units with the concepts described in detail with derivations presented. The author puts the emphasis on computational aspects of optimization and includes design examples and problems representing different areas of engineering. Comprehensive in scope, the book contains solved examples, review questions and problems. This important book:
- Offers an updated edition of the classic work on optimization
- Includes approaches that are appropriate for all branches of engineering
- Contains numerous practical design and engineering examples
- Offers more than 140 illustrative examples, 500 plus references in the literature of engineering optimization, and more than 500 review questions and answers
- Demonstrates the use of MATLAB for solving different types of optimization problems using different techniques
Written for students across all engineering disciplines, the revised edition ofĀ Engineering Optimization: Theory and PracticeĀ is the comprehensive book that covers the new and recent methods of optimization and reviews the principles and applications.
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Information
Table of contents
- Cover
- Table of Contents
- Preface
- Acknowledgment
- About the Author
- 1 Introduction to Optimization
- 2 Classical Optimization Techniques
- 3 Linear Programming I: Simplex Method
- 4 Linear Programming II: Additional Topics and Extensions
- 5 Nonlinear Programming I: OneāDimensional Minimization Methods
- 6 Nonlinear Programming II: Unconstrained Optimization Techniques
- 7 Nonlinear Programming III: Constrained Optimization Techniques
- 8 Geometric Programming
- 9 Dynamic Programming
- 10 Integer Programming
- 11 Stochastic Programming
- 12 Optimal Control and Optimality Criteria Methods
- 13 Modern Methods of Optimization
- 14 Metaheuristic Optimization Methods
- 15 Practical Aspects of Optimization
- 16 Multilevel and Multiobjective Optimization
- 17 Solution of Optimization Problems Using MATLAB
- Appendix A: Appendix AConvex and Concave FunctionsConvex and Concave Functions
- Appendix B: Appendix BSome Computational Aspects of OptimizationSome Computational Aspects of Optimization
- Appendix C: Appendix CIntroduction to MATLABĀ®Introduction to MATLABĀ®
- Answers to Selected Problems
- Index
- End User License Agreement