DocumentCode
2350413
Title
Optimizing lineage information in genetic algorithms for producing superior models
Author
Boetticher, Gary D. ; Rudisill, Jason
Author_Institution
University of Houston ¿ Clear Lake, Houston, TX 77058, USA
fYear
2008
fDate
13-15 July 2008
Firstpage
314
Lastpage
318
Abstract
A lot of research in the area of genetic algorithms (GA) is applied, but little research examines the impact of lineage information in optimizing a GA. Normally, researchers consider primarily elitism, an approach which carries only a very small fixed subset of the population to the next generation, as a lineage strategy. This paper investigates several different lineage percentages (what percent of the population to carry forward) to determine an ideal percentage or range from improving the accuracy of a GA. Several experiments are performed, and all results are statistically validated.
Keywords
Biological cells; Chromosome mapping; Couplings; Equations; Genetic algorithms; Genetic mutations; Lakes; Learning systems; Noise generators; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Reuse and Integration, 2008. IRI 2008. IEEE International Conference on
Conference_Location
Las Vegas, NV, USA
Print_ISBN
978-1-4244-2659-1
Electronic_ISBN
978-1-4244-2660-7
Type
conf
DOI
10.1109/IRI.2008.4583049
Filename
4583049
Link To Document