Abstract
Spatially structured evolutionary algorithms (EAs) have shown to be endowed with useful features for global optimization. Distributed EAs (dEA) and cellular EAs (cEA) are two of the most widely known types of structured algorithms. In this paper we deal with cellular EAs. Two important parameters guiding the search in a cEA are the population topology and the neighborhood defined on it. Here we first review some theoretical results which show that a cEA with a 2D grid can be easily tuned to shift from exploration to exploitation. We initially make a study on the relationship between the topology and the neighborhood by defining a ratio measure between they two. Then, we encompass a set of tests aimed at discovering the performance that different ratio values have on different classes of problems. We find out that, with the same neighborhood, rectangular grids have some advantages in multimodal and epistatic problems, while square ones are more efficient for solving deceptive problems and for simple function optimization. Finally, we propose and study a cEA in which the ratio is dynamically changed.
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
Alba E. and Troya J.M.: A Survey of Parallel Distributed Genetic Algorithms. Complexity, John Wiley & Sons (1999) 4(4):31–52
Alba E. and Troya J.M.: Influence of the Migration Policy in Parallel Distributed GAs with Structured and Panmictic Populations. Applied Intelligence 12(3) (2000) 163–181
Alba E., Cotta C, and Troya J.M.: On the Importance of the Grid Shape in 2D Spatially Structured GAs. Journal of Evolutionary Optimization (2000) to appear
Bäck T., Fogel D., and Michalewicz Z. (eds.) Handbook of Evolutionary Computation. Oxford University Press (1997)
Baluja S.: Structure and Performance of Fine-Grain Parallelism in Genetic Search. In: Proceedings of the 5th International Conference on Genetic Algorithms, Forrest S. (ed.). Morgan Kaufmann (1993) 155–162
De Jong K.A., Potter M.A., and Spears W.M.: Using Problem Generators to Explore the Effects of Epistasis. In: Proceedings of the 7th International Conference of Genetic Algorithms, Back T. (ed.). Morgan Kaufmann (1997) 338–345
Goldberg D.E., Deb K., and Horn J. Massively Multimodality, Deception and Genetic Algorithms. In: Proceedings of the PPSN II, Männer R., Manderick B. (eds.). North-Holland (1992)37–46
Gordon V.S. and Whitley D.: Serial and Parallel Genetic Algorithms as Function Optimizers. In: Proceedings of the 5th International Conference on Genetic Algorithms, Forrest S. (ed.). Morgan Kaufmann (1993) 177–183
Mühienbein H., Schomisch M., and Born J.: The Parallel Genetic Algorithm as Function Optimizer. In: Proceedings of the 4th International Conference on Genetic Algorithms, Belew R.K., Booker L.B. (eds.). Morgan Kaufmann (1991) 271–278
Sarma J. and De Jong K.A.: An Analysis of the Effects of Neighborhood Size and Shape on Local Selection Algorithms. In: Proceedings of the PPSN IV, Voigt H.M., Ebeling W., Re-chenberg I., and Schwefel H.P. (eds.). Springer-Verlag (1996) 236–244
Sarma J. and De Jong K.A.: An Analysis of Local Selection Algorithms in a Spatially Structured Evolutionary Algorithm. In: Proceedings of the 7th International Conference on Genetic Algorithms, Bäck T. (ed.). Morgan Kaufmann (1997) 181–186
Spiessens P. and Manderick B.: A Massively Parallel Genetic Algorithm. In: Proceedings of the 4th International Conference on Genetic Algorithms, Belew R.K., Booker L.B. (eds.). Morgan Kaufmann (1991) 279–286
Tomassini M.: The Parallel Genetic Cellular Automata: Application to Global Function Optimization. In: Proceedings of the International Conference on Artificial Neural Nets and GAs, Albretch R.F., Reeves C.R., Steele N.C. (eds.). Springer-Verlag (1993) 385–391
Tsutsui S., Ghosh A., Come D., Fujimoto Y.: A Real Coded Genetic Algorithm with an Explorer and an Exploiter Populations. In: Proceedings of the Seventh ICGA, Bäck T. (ed.). Morgan Kaufmann (1997) 238–245
Whitley D.: Cellular Genetic Algorithms. In: Proceedings of the 5th International Conference on Genetic Algorithms, Forrest S. (ed.). Morgan Kaufmann (1993) 658
Wolpert D.H., W.G. Macready: No Free Lunch Theorems for Optimization. IEEE Transactions on Evolutionary Computation 1(1) (1997) 67–82
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Alba, E., Troya, J.M. (2000). Cellular Evolutionary Algorithms: Evaluating the Influence of Ratio. In: Schoenauer, M., et al. Parallel Problem Solving from Nature PPSN VI. PPSN 2000. Lecture Notes in Computer Science, vol 1917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45356-3_3
Download citation
DOI: https://doi.org/10.1007/3-540-45356-3_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-41056-0
Online ISBN: 978-3-540-45356-7
eBook Packages: Springer Book Archive