Abstract
Recently, the methodologies of multi-parent crossover have been developed by performing the crossover operation with multi-parent. Some studies have indicated the high performance of multi-parent crossover on some numerical optimization problems. Here a new crossover operator has been proposed by integrating multi-parent crossover with the approach of experimental design. It is based on experimental design method in exploring the solution space that compensates the random search as in traditional genetic algorithm. By replacing the inbuilt randomness of crossover operator with a more systematical method, the proposed method outperforms the classical GA strategy on several GA benchmark problems.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
T. Back, Evolutionary algorithms in theory and practice. Oxford University Press, New York, 1996.
W. G. Cochran, G. M. Cox, Experimental designs, John Wiley and Sons, 1957.
J. Denes, A. D. Keedwell, Latin squares and their application, Academic Press, 1974.
A. E. Eiben, H. M. Kemenade, Diagonal crossover in genetic algorithms for numerical optimization, Journal of Control and Cybernetics, pp. 447–465, vol. 26, no. 3, 1997.
A. E. Eiben, P. E. Raue, Zs. Ruttkay, Genetic algorithms with multi-parent recombination, Proceedings of the third Conference on Parallel Problem Solving from Nature, Springer-Verlay, pp. 78–87, 1994.
D. Goldberg, Genetic algorithms in search, optimization and machine learning, Addison-Wesley, 1989.
K. A. De Jong, An analysis of the behavior of a class of genetic adaptive systems, Ph.D. Thesis, University of Michigan, Ann Arbor, MI., 1975.
C. F. Laywine, G. L. Mullen, Discrete mathematics using Latin squares, A Wiley Interscience Publication, 1998.
Z. Michalewicz, Genetic algorithms+Data structures=Evolution programs, Springer-Verlag, 1992.
M. W. Spears, K. DeJong, An analysis of multi-point crossover, Foundations of Genetic Algorithms, pp. 301–315, 1991.
S. Tsutsui, A. Ghosh, A study on the effect of multi-parent recombination in real coded genetic algorithms, Proceedings of the Second International Conference on Knowledge-Based Intelligent Electronic Systems, vol. 3, pp. 155–160, 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chan, K.Y., Fogarty, T.C. (2003). Experimental Design Based Multi-parent Crossover Operator. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E., Poli, R., Costa, E. (eds) Genetic Programming. EuroGP 2003. Lecture Notes in Computer Science, vol 2610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36599-0_27
Download citation
DOI: https://doi.org/10.1007/3-540-36599-0_27
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00971-9
Online ISBN: 978-3-540-36599-0
eBook Packages: Springer Book Archive