Introduction to Evolutionary Computing
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The Basics
1. Problems to be Solved
2. Evolutionary Computing: The Origins
3. What is an Evolutionary Algorithm?
4. Representation, Mutation, and Recombination
5. Fitness, Selection, and Population Management
6. Popular Evolutionary Algorithm Variants
Methodology
7. Parameters and Parameter Tuning
8. Parameter Control
9. Working with Evolutionary Algorithms
Advanced Topics
10. Hybridisation with Other Techniques: Memetic Algorithms
11. Nonstationary and Noisy Function Optimisation
12. Multiobjective Evolutionary Algorithms
13. Constraint Handling
14. Interactive Evolutionary Algorithms
15. Coevolutionary Systems
16. Theory
17. Evolutionary Robotics
About Us
Exercises
Exercises for Chapter One: Problems
Exercises for Chapter Two: EC Origins
Exercises for Chapter Three: What is an EA?
Exercises for Chapter Four: Representation, Recombination and Mutation
Exercises for Chapter Five: Fitness, Selection, and Population Management
Exercises for Chapter Seven: Parameters and Parameter Tuning
Exercises for Chapter Eight: Parameter Control
Exercises for Chapter Nine: Working with Evolutionary Algorithms
Exercises for Chapter Ten: Memetic Algorithms
Exercises for Chapter Eleven: Nonstationary and Noisy Function Optimisation
Exercises for Chapter Twelve: Multiobjective Evolutionary Algorithms
Exercises for Chapter 13: Constraint Handling
Exercises for Chapter 14: Interactive EAs
Exercises for Chapter 15: Coevolutionary Systems
Exercises for Chapter 16: Theory
Additional Materials
Suggested Reading for Chapter One: Problems
Suggested Reading for Chapter Two: Origins of EC
Suggested Reading for Chapter Three: What is an EA?
Suggested Reading for Chapter Four: Representation, Mutation and Recombination
Suggested Reading for Chapter Five: Fitness, Selection and Population Management
Suggested Reading for Chapter Six: Popular Evolutionary Algorithm Variants
Suggested Reading for Chapter Seven: Parameters and Parameter Tuning
Suggested Reading for Chapter Eight: Parameter Control
Suggested Reading for Chapter Nine: Working with EAs
Suggested Reading for Chapter Ten: Memetic Algorithms
Suggested Reading for Chapter Eleven: Nonstationary and Noisy Function Optimisation
Suggested Reading for Chapter Twelve: Multiobjective Evolutionary Algorithms
Suggested Reading for Chapter 13: Constraint Handling
Suggested Reading for Chapter 14: Interactive EAs
Suggested Reading for Chapter 15: Coevolutionary Systems
Suggested Reading for Chapter 16: Theory
Suggested Reading for Chapter 17: Evolutionary Robotics
Slides
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About Us
We are Jim and Gusz
The on-line accompaniment to the book Introduction to Evolutionary Computing