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
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;
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
DOI :
10.1109/CEC.2008.4630819