PhD thesis,
The parameter-less genetic algorithm: Rational and automated parameter selection for simplified genetic algorithm operation
Universidade Nova de Lisboa, Portugal, (2000)
Abstract
Genetic algorithms (GAs) have been used to solve difficult optimization
problems in a number of fields. One of the advantages of these algorithms
is that they operate well even in domains where little is known, thus giving
the GA the flavor of a general purpose problem solver. However, in order
to solve a problem with the GA, the user usually has to specify a number
of parameters that have little to do with the user's problem, and have more
to do with the way the GA operates. This dissertation presents a technique
that greatly simplifies the GA operation by relieving the user from having
to set these parameters. Instead, the parameters are set automatically by
the algorithm itself. The validity of the approach is illustrated with artificial
problems often used to test GA techniques, and also with a simplified version
of a network expansion problem
