Cover image for Engineering Optimization, 5th Edition

Engineering Optimization, 5th Edition

Author Singiresu S. Rao
Release Date: 2019/11/01
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Book Description

The revised and updated new edition of the popular optimization book for engineers

The thoroughly revised and updated fifth edition of Engineering Optimization: Theory and Practice offers engineers a guide to the important optimization methods that are commonly used in a wide range of industries. The author—a noted expert on the topic—presents 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, and is accompanied by a website hosting a solutions manual. 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 of Engineering Optimization: Theory and Practice is the comprehensive book that covers the new and recent methods of optimization and reviews the principles and applications.

Table of Contents

  1. Cover
  2. Preface
    1. Features
    2. Contents
  3. Acknowledgment
  4. About the Author
  5. About the Companion Website
  6. 1 Introduction to Optimization
    1. 1.1 Introduction
    2. 1.2 Historical Development
    3. 1.3 Engineering Applications of Optimization
    4. 1.4 Statement of An Optimization Problem
    5. 1.5 Classification of Optimization Problems
    6. 1.6 Optimization Techniques
    7. 1.7 Engineering Optimization Literature
    8. 1.8 Solutions Using MATLAB
    9. References and Bibliography
    10. Review Questions
    11. Problems
  7. 2 Classical Optimization Techniques
    1. 2.1 Introduction
    2. 2.2 Single‐Variable Optimization
    3. 2.3 Multivariable Optimization with no Constraints
    4. 2.4 Multivariable Optimization with Equality Constraints
    5. 2.5 Multivariable Optimization with Inequality Constraints
    6. 2.6 Convex Programming Problem
    7. References and Bibliography
    8. Review Questions
    9. Problems
  8. 3 Linear Programming I: Simplex Method
    1. 3.1 Introduction
    2. 3.2 Applications of Linear Programming
    3. 3.3 Standard form of a Linear Programming Problem
    4. 3.4 Geometry of Linear Programming Problems
    5. 3.5 Definitions and Theorems
    6. 3.6 Solution of a System of Linear Simultaneous Equations
    7. 3.7 Pivotal Reduction of a General System of Equations
    8. 3.8 Motivation of the Simplex Method
    9. 3.9 Simplex Algorithm
    10. 3.10 Two Phases of the Simplex Method
    11. 3.11 Solutions Using MATLAB
    12. References and Bibliography
    13. Review Questions
    14. Problems
  9. 4 Linear Programming II: Additional Topics and Extensions
    1. 4.1 Introduction
    2. 4.2 Revised Simplex Method
    3. 4.3 Duality in Linear Programming
    4. 4.4 Decomposition Principle
    5. 4.5 Sensitivity or Postoptimality Analysis
    6. 4.6 Transportation Problem
    7. 4.7 Karmarkar's Interior Method
    8. 4.8 Quadratic Programming
    9. 4.9 Solutions Using Matlab
    10. References and Bibliography
    11. Review Questions
    12. Problems
  10. 5 Nonlinear Programming I: One‐Dimensional Minimization Methods
    1. 5.1 Introduction
    2. 5.2 Unimodal Function
    3. 5.3 Unrestricted Search
    4. 5.4 Exhaustive Search
    5. 5.5 Dichotomous Search
    6. 5.6 Interval Halving Method
    7. 5.7 Fibonacci Method
    8. 5.8 Golden Section Method
    9. 5.9 Comparison of Elimination Methods
    10. 5.10 Quadratic Interpolation Method
    11. 5.11 Cubic Interpolation Method
    12. 5.12 Direct Root Methods
    13. 5.13 Practical Considerations
    14. 5.14 Solutions Using MATLAB
    15. References and Bibliography
    16. Review Questions
    17. Problems
  11. 6 Nonlinear Programming II: Unconstrained Optimization Techniques
    1. 6.1 Introduction
    2. 6.2 Random Search Methods
    3. 6.3 Grid Search Method
    4. 6.4 Univariate Method
    5. 6.5 Pattern Directions
    6. 6.6 Powell's Method
    7. 6.7 Simplex Method
    8. 6.8 Gradient of a Function
    9. 6.9 Steepest Descent (CAuchy) Method
    10. 6.10 Conjugate Gradient (FLetcher–REeves) Method
    11. 6.11 Newton's Method
    12. 6.12 MArquardt Method
    13. 6.13 Quasi‐Newton Methods
    14. 6.14 DAvidon–FLetcher–POwell Method
    15. 6.15 BRoyden–FLetcher–GOldfarb–SHanno Method
    16. 6.16 Test Functions
    17. 6.17 Solutions Using Matlab
    18. References and Bibliography
    19. Review Questions
    20. Problems
  12. 7 Nonlinear Programming III: Constrained Optimization Techniques
    1. 7.1 Introduction
    2. 7.2 Characteristics of a Constrained Problem
    3. 7.3 Random Search Methods
    4. 7.4 Complex Method
    5. 7.5 Sequential Linear Programming
    6. 7.6 Basic Approach in the Methods of Feasible Directions
    7. 7.7 Zoutendijk's Method of Feasible Directions
    8. 7.8 Rosen's Gradient Projection Method
    9. 7.9 Generalized Reduced Gradient Method
    10. 7.10 Sequential Quadratic Programming
    11. 7.11 Transformation Techniques
    12. 7.12 Basic Approach of the Penalty Function Method
    13. 7.13 Interior Penalty Function Method
    14. 7.14 Convex Programming Problem
    15. 7.15 Exterior Penalty Function Method
    16. 7.16 Extrapolation Techniques in the Interior Penalty Function Method
    17. 7.17 Extended Interior Penalty Function Methods
    18. 7.18 Penalty Function Method for Problems with Mixed Equality and Inequality Constraints
    19. 7.19 Penalty Function Method for Parametric Constraints
    20. 7.20 Augmented Lagrange Multiplier Method
    21. 7.21 Checking the Convergence of Constrained Optimization Problems
    22. 7.22 Test Problems
    23. 7.23 Solutions Using MATLAB
    24. References and Bibliography
    25. Review Questions
    26. Problems
  13. 8 Geometric Programming
    1. 8.1 Introduction
    2. 8.2 Posynomial
    3. 8.3 Unconstrained Minimization Problem
    4. 8.4 Solution of an Unconstrained Geometric Programming Program using Differential Calculus
    5. 8.5 Solution of an Unconstrained Geometric Programming Problem Using Arithmetic–Geometric Inequality
    6. 8.6 Primal–dual Relationship and Sufficiency Conditions in the Unconstrained Case
    7. 8.7 Constrained Minimization
    8. 8.8 Solution of a Constrained Geometric Programming Problem
    9. 8.9 Primal and Dual Programs in the Case of Less‐than Inequalities
    10. 8.10 Geometric Programming with Mixed Inequality Constraints
    11. 8.11 Complementary Geometric Programming
    12. 8.12 Applications of Geometric Programming
    13. References and Bibliography
    14. Review Questions
    15. Problems
  14. 9 Dynamic Programming
    1. 9.1 Introduction
    2. 9.2 Multistage Decision Processes
    3. 9.3 Concept of Suboptimization and Principle of Optimality
    4. 9.4 Computational Procedure in Dynamic Programming
    5. 9.5 Example Illustrating the Calculus Method of Solution
    6. 9.6 Example Illustrating the Tabular Method of Solution
    7. 9.7 Conversion of a Final Value Problem into an Initial Value Problem
    8. 9.8 Linear Programming as a Case of Dynamic Programming
    9. 9.9 Continuous Dynamic Programming
    10. 9.10 Additional Applications
    11. References and Bibliography
    12. Review Questions
    13. Problems
  15. 10 Integer Programming
    1. 10.1 Introduction
    2. 10.2 Graphical Representation
    3. 10.3 Gomory's Cutting Plane Method
    4. 10.4 Balas' Algorithm for Zero–One Programming Problems
    5. 10.5 Integer Polynomial Programming
    6. 10.6 Branch‐and‐Bound Method
    7. 10.7 Sequential Linear Discrete Programming
    8. 10.8 Generalized Penalty Function Method
    9. 10.9 Solutions Using MATLAB
    10. References and Bibliography
    11. Review Questions
    12. Problems
  16. 11 Stochastic Programming
    1. 11.1 Introduction
    2. 11.2 Basic Concepts of Probability Theory
    3. 11.3 Stochastic Linear Programming
    4. 11.4 Stochastic Nonlinear Programming
    5. 11.5 Stochastic Geometric Programming
    6. References and Bibliography
    7. Review Questions
    8. Problems
  17. 12 Optimal Control and Optimality Criteria Methods
    1. 12.1 Introduction
    2. 12.2 Calculus of Variations
    3. 12.3 Optimal Control Theory
    4. 12.4 Optimality Criteria Methods
    5. References and Bibliography
    6. Review Questions
    7. Problems
  18. 13 Modern Methods of Optimization
    1. 13.1 Introduction
    2. 13.2 Genetic Algorithms
    3. 13.3 Simulated Annealing
    4. 13.4 Particle Swarm Optimization
    5. 13.5 Ant Colony Optimization
    6. 13.6 Optimization of Fuzzy Systems
    7. 13.7 Neural‐Network‐Based Optimization
    8. References and Bibliography
    9. Review Questions
    10. Problems
  19. 14 Metaheuristic Optimization Methods
    1. 14.1 Definitions
    2. 14.2 Metaphors Associated with Metaheuristic Optimization Methods
    3. 14.3 Details of Representative Metaheuristic Algorithms
    4. References and Bibliography
    5. Review Questions
  20. 15 Practical Aspects of Optimization
    1. 15.1 Introduction
    2. 15.2 Reduction of Size of an Optimization Problem
    3. 15.3 Fast Reanalysis Techniques
    4. 15.4 Derivatives of Static Displacements and Stresses
    5. 15.5 Derivatives of Eigenvalues and Eigenvectors
    6. 15.6 Derivatives of Transient Response
    7. 15.7 Sensitivity of Optimum Solution to Problem Parameters
    8. References and Bibliography
    9. Review Questions
    10. Problems
  21. 16 Multilevel and Multiobjective Optimization
    1. 16.1 Introduction
    2. 16.2 Multilevel Optimization
    3. 16.3 Parallel Processing
    4. 16.4 Multiobjective Optimization
    5. 16.5 Solutions Using MATLAB
    6. References and Bibliography
    7. Review Questions
    8. Problems
  22. 17 Solution of Optimization Problems Using MATLAB
    1. 17.1 Introduction
    2. 17.2 Solution of General Nonlinear Programming Problems
    3. 17.3 Solution of Linear Programming Problems
    4. 17.4 Solution of LP Problems Using Interior Point Method
    5. 17.5 Solution of Quadratic Programming Problems
    6. 17.6 Solution of One‐Dimensional Minimization Problems
    7. 17.7 Solution of Unconstrained Optimization Problems
    8. 17.8 Solution of Constrained Optimization Problems
    9. 17.9 Solution of Binary Programming Problems
    10. 17.10 Solution of Multiobjective Problems
    11. References and Bibliography
    12. Problems
  23. Appendix A: Appendix AConvex and Concave FunctionsConvex and Concave Functions
  24. Appendix B: Appendix BSome Computational Aspects of OptimizationSome Computational Aspects of Optimization
    1. B.1 Choice of Method
    2. B.2 Comparison of Unconstrained Methods
    3. B.3 Comparison of Constrained Methods
    4. B.4 Availability of Computer Programs
    5. B.5 Scaling of Design Variables and Constraints
    6. B.6 Computer Programs for Modern Methods of Optimization
    7. References and Bibliography
  25. Appendix C: Appendix CIntroduction to MATLAB®Introduction to MATLAB®
    1. C.1 Features and Special Characters
    2. C.2 Defining Matrices in MATLAB
    3. C.3 Creating m‐Files
    4. C.4 Optimization Toolbox
  26. Answers to Selected Problems
    1. CHAPTER 1
    2. CHAPTER 2
    3. CHAPTER 3
    4. CHAPTER 4
    5. CHAPTER 5
    6. CHAPTER 6
    7. CHAPTER 7
    8. CHAPTER 8
    9. CHAPTER 9
    10. CHAPTER 10
    11. CHAPTER 11
    12. CHAPTER 12
    13. CHAPTER 13
    14. CHAPTER 15
    15. CHAPTER 16
  27. Index
  28. End User License Agreement
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