The Simple Genetic Algorithm

Foundations and Theory
Overview

The Simple Genetic Algorithm (SGA) is a classical form of genetic search. Viewing the SGA as a mathematical object, Michael D. Vose provides an introduction to what is known (i.e., proven) about the theory of the SGA. He also makes available algorithms for the computation of mathematical objects related to the SGA. Although he describes the SGA in terms of heuristic search, the book is not about search or optimization per se. Rather, the focus is on the SGA as an evolutionary system. The author intends the book also to serve as an outline for exploring topics in mathematics and computer science in a goal-oriented way.

Table of Contents

  1. Preface
  2. Acknowledgments
  3. 1. Introduction
  4. 2. Notation
  5. 3. Random Heuristic Search
  6. 4. The Simple Genetic Algorithm
  7. 5. Implementation
  8. 6. The Walsh Transform
  9. 7. Computing with the Heuristic
  10. 8. Basic Examples
  11. 9. The Inverse Heuristic
  12. 10. Focused Heuristics
  13. 11. Linear Fitness
  14. 12. Perturbation Arguments
  15. 13. Transient Behavior
  16. 14. Asymptotic Behavior
  17. 15. Hyperbolicity
  18. 16. Geometric Invariance
  19. 17. Quotients
  20. 18. Models
  21. 19. Schemata
  22. 20. Appendix
  23. Theorem Index
  24. Symbol Index
  25. Index