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