A Comparison of Selection Schemes Used in Genetic
Algorithms
TIK-Report, 11. TIK Institut fur Technische Informatik und
Kommunikationsnetze, Computer Engineering and Networks
Laboratory, ETH, Swiss Federal Institute of
Technology, Gloriastrasse 35, 8092 Zurich, Switzerland, (December 1995)Abstract
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.