DocumentCode
2909799
Title
Crossover operators to control size growth in linear GP and variable length GAs
Author
Chu, Dominique ; Rowe, Jonathan E.
Author_Institution
Comput. Lab., Univ. of Kent, Canterbury
fYear
2008
fDate
1-6 June 2008
Firstpage
336
Lastpage
343
Abstract
In various nuances of evolutionary algorithms it has been observed that variable sized genomes exhibit large degrees of redundancy and corresponding undue growth. This phenomenon is commonly referred to as ldquobloat.rdquo The present contribution investigates the role of crossover operators as the cause for length changes in variable length genetic algorithms and linear GP. Three crossover operators are defined; each is tested with three different fitness functions. The aim of this article is to indicate suitable designs of crossover operators that allow efficient exploration of designs of solutions of a wide variety of sizes, while at the same time avoiding bloat.
Keywords
genetic algorithms; linear programming; redundancy; crossover operators; evolutionary algorithms; genetic algorithms; linear GP; redundancy; size growth control; variable length GA; Bioinformatics; Biological information theory; Chemicals; Control systems; Evolution (biology); Evolutionary computation; Genetic algorithms; Genetic programming; Genomics; Size control;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-1822-0
Electronic_ISBN
978-1-4244-1823-7
Type
conf
DOI
10.1109/CEC.2008.4630819
Filename
4630819
Link To Document