Evolutionary Computation


This page contains resources about Genetic Algorithms, Evolutionary Computation, Swarm Intelligence and Population-Based Metaheuristics in general.

More specific information is included in each subfield.

Subfields and Concepts

  • Evolutionary Algorithms
  • Genetic Algorithms
  • Genetic Programming
  • Particle Swarm Optimization
  • Swarm Algorithms
  • Ant Colony Optimization
  • Evolutionary Inductive Turing Machines
  • Evolutionary Automata

Online Courses

Video Lectures

Lecture Notes

Books and Book Chapters

See also Bibliography

  • Sheppard, C. (2016). Genetic Algorithms with Python. CreateSpace.
  • Luke, S. (2009). Essentials of Metaheuristics. Lulu.
  • Poli, R., Langdon, W. B., McPhee, N. F., & Koza, J. R. (2008). A field guide to genetic programming. Lulu.
  • Sivanandam, S. N., & Deepa, S. N. (2008). Introduction to genetic algorithms. Springer.
  • Brabazon, A., & O'Neill, M. (2006). Biologically inspired algorithms for financial modelling. Springer Science & Business Media.
  • Haupt, R. L., & Haupt, S. E. (2004). Practical genetic algorithms. John Wiley & Sons.
  • Eiben, A. E., & Smith, J. E. (2003). Introduction to evolutionary computing. Springer Science & Business Media.
  • Bäck, T., Fogel, D. B., & Michalewicz, Z. (Eds.). (2000). Evolutionary computation 1: Basic algorithms and operators (Vol. 1). CRC Press.
  • Bäck, T., Fogel, D. B., & Michalewicz, Z. (Eds.). (2000). Evolutionary computation 12: Advanced Algorithms and Operators (Vol. 2). Taylor & Francis.
  • Mitchell, T. M. (1997). "Chapter 9: Genetics Algorithms". Machine Learning. McGraw Hill.
  • Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley.

Scholarly Articles


See also

Other Resources