Small Population Effects and Hybridization

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Ashlock5:2008:cec,

• author = "Daniel A. Ashlock and Kenneth M. Bryden and Steven Corns",
• title = "Small Population Effects and Hybridization",
• booktitle = "2008 IEEE World Congress on Computational Intelligence",
• year = "2008",
• editor = "Jun Wang",
• pages = "2637--2643",
• address = "Hong Kong",
• month = "1-6 " # jun,
• organization = "IEEE Computational Intelligence Society",
• publisher = "IEEE Press",
• isbn13 = "978-1-4244-1823-7",
• file = "EC0599.pdf",
• DOI = "doi:10.1109/CEC.2008.4631152",
• size = "7 pages",
• abstract = "This paper examines the confluence of two lines of research that seek to improve the performance of evolutionary computation systems through management of information flow. The first is hybridisation; the second is using small population effects. Hybridisation consists of restarting evolutionary algorithms with copies of bestof- population individuals drawn from many populations. Small population effects occur when an evolutionary algorithm's performance, either speed or probability of premature convergence, is improved by use of a very small population. This paper presents a structure for evolutionary computation called a blender which performs hybridisation of many small populations. The blender algorithm is tested on the PORS and Tartarus tasks. Substantial and significant effects result from varying the size of the small populations used and from varying the frequency with which hybridisation is performed. The major effect results from changing the frequency of hybridization; the impact of population size is more modest. The parameter settings which yield best performance of the blender algorithm are remarkably consistent across all seven sets of experiments performed. Blender performance is found to be superior to other algorithms for six cases of the PORS problem. For Tartarus, blender performs well, but not as well as the previous hybridization experiments that motivated its development.",
• keywords = "genetic algorithms, genetic programming",
• notes = "WCCI 2008 - A joint meeting of the IEEE, the INNS, the EPS and the IET.",

}

Genetic Programming entries for Daniel Ashlock Kenneth M Bryden Steven M Corns

Citations