Created by W.Langdon from gp-bibliography.bib Revision:1.4812
Genetic Algorithms are a common probabilistic optimization method based on the model of natural evolution. One important operator in these algorithms is the selection scheme for which a new description model is introduced in this paper. With this a mathematical analysis of tournament selection, truncation selection, linear and exponential ranking selection and proportional selection is carried out that allows an exact prediction of the fitness values after selection. The further analysis derives the selection intensity, selection variance, and the loss of diversity for all selection schemes. For completion a pseudo- code formulation of each method is included. The selection schemes are compared and evaluated according to their properties leading to an unified view of these different selection schemes. Furthermore the correspondence of binary tournament selection and ranking selection in the expected fitness distribution is proven.",
Of special interest for the GP community may be the fact that in this report three analytic approximation formulas are obtained using GP for symbolic regression. The method is described in appendix A of the report.
Second (extended and corrected) edition available via www and ftp Dec 1995
Genetic Programming entries for Tobias Blickle Lothar Thiele