Abstract
A Compact Genetic Algorithm (CGA) is a genetic algorithm specially devised to meet the tight restrictions of hardware-based implementations. We propose a new mutation operator for an elitism-based CGA. The performance of this algorithm, named emCGA, was tested using a set of algebraic functions for optimization. The optimal mutation rate found for high-dimensionality functions is around 0.5%, and the low the dimension of the problem, the less sensitive is emCGA to the mutation rate. The emCGA was compared with other two similar algorithms and demonstrated better tradeoff between quality of solutions and convergence speed. It also achieved such results with smaller population sizes than the other algorithms.
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
Ahn, C., Ramakrishna, R.: Elitism-based compact genetic algorithms. IEEE Trans. Evolutionary Computation 7, 367–385 (2003)
Becker, J., Hartenstein, R.: Configware and morphware going mainstream. J. Systems Architecture 49, 127–142 (2003)
Gallagher, J., Vigraham, S., Kramer, G.: A family of compact genetic algorithms for intrinsic evolvable hardware. IEEE Trans. Evolutionary Computation 8, 111–126 (2004)
Goldberg, D.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison Wesley, Reading (1989)
Harik, G., Lobo, F., Goldberg, D.: The compact genetic algorithm. In: Proc. IEEE Conf. on Evolutionary Computation, pp. 523–528 (1998)
Krink, T., Filipic, B., Fogel, G., Thompsen, R.: Noisy optimization problems – a particular challenge for differential evolution? In: Proc. IEEE Conf. on Evolutionary Computation, pp. 332–339 (2004)
Lopes, H.S., Moritz, G.L.: A graph-based genetic algorithm for the multiple sequence alignment problem. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds.) ICAISC 2006. LNCS (LNAI), vol. 4029, pp. 420–429. Springer, Heidelberg (2006)
Moritz, G.L., Jory, C., Lopes, H.S., Erig Lima, C.R.: Implementation of a parallel algorithm for pairwise alignment using reconfigurable computing. In: Proc. IEEE Int. Conf. on Reconfigurable Computing and FPGAs, pp. 99–105 (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Silva, R.R., Lopes, H.S., Erig Lima, C.R. (2007). A New Mutation Operator for the Elitism-Based Compact Genetic Algorithm. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71618-1_18
Download citation
DOI: https://doi.org/10.1007/978-3-540-71618-1_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71589-4
Online ISBN: 978-3-540-71618-1
eBook Packages: Computer ScienceComputer Science (R0)