Evolutionary Computation



This page contains resources about Genetic Algorithms and  Evolutionary Computation in general.

More specific information is included in each subfield.

Subfields and Concepts
See Category:Evolutionary Computation for some of  its subfields.
 * Genetic Algorithms

Lecture Notes

 * Evolutionary Computation by Fernando Lobo

Books
See also Bibliography
 * Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley.


 * Mitchell, T. M. (1997). "Chapter 9: Genetics Algorithms". Machine Learning. McGraw Hill.


 * 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.
 * Eiben, A. E., & Smith, J. E. (2003). Introduction to evolutionary computing. Springer Science & Business Media.
 * Haupt, R. L., & Haupt, S. E. (2004). Practical genetic algorithms. John Wiley & Sons.
 * 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.

Software

 * Genetic Algorithm - MATLAB
 * MCMLL - C++
 * Evolver - proprietary software that solves optimization problems using a genetic algorithm

Other Resources

 * Evolutionary Computation - Notebook