Abstract
The fundamental steps of the gene expression algorithm (GEA) are schematically represented in Figure 3.1. The process begins with the random generation of the chromosomes of a certain number of individuals (the initial population). Then these chromosomes are expressed and the fitness of each individual is evaluated against a set of fitness cases (also called selection environment which, in fact, is the input to a problem). The individuals are then selected according to their fitness (their performance in that particular environment) to reproduce with modification, leaving progeny with new traits. These new individuals are, in their turn, subjected to the same developmental process: expression of the genomes, confrontation of the selection environment, selection, and reproduction with modification. The process is repeated for a certain number of generations or until a good solution has been found.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer
About this chapter
Cite this chapter
Ferreira, C. (2006). The Basic Gene Expression Algorithm. In: Gene Expression Programming. Studies in Computational Intelligence, vol 21. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32849-1_3
Download citation
DOI: https://doi.org/10.1007/3-540-32849-1_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32796-7
Online ISBN: 978-3-540-32849-0
eBook Packages: EngineeringEngineering (R0)