Optimization in Practice with MATLAB for Engineering Students and Professionals (2015)

Part I: Helpful Preliminaries

Chapter 1: MATLAB as a Computation Tool

Chapter 2: Mathematical Preliminaries

Part II: Using Optimization - The Road Map

Chapter 3: Welcome to the Fascinating World of Optimization

Chapter 4: Analysis, Design, Optimization, and Modeling

Chapter 5: Introducing Linear and Nonlinear Programming

Part III: Using Optimization - Practical Essentials

Chapter 6: Multiobjective Optimization

Chapter 7: Numerical Essentialss

Chapter 8: Global Optimization Basics

Chapter 9: Discrete Optimization Basics

Chapter 10: Practicing Optimization – Larger Examples

Part IV: Going Deeper: Inside the Codes and Theoretical Aspects

Chapter 11: Linear Programming

Chapter 12: Nonlinear Programming with No Constraints

Chapter 13: Nonlinear Programming with Constraints

Part V: More Advanced Topics in Optimization

Chapter 14: Discrete Optimization

Chapter 15: Modeling Complex Systems: Surrogate Modeling and Design Space Reduction

Chapter 16: Design Optimization Under Uncertainty

Chapter 17: Methods for Pareto Frontier Generation/Representation

Chapter 18: Physical Programming for Multiobjective Optimization

Chapter 19: Evolutionary Algorithms