Abstract
To solve GA-difficult problems in which we cannot ensure tight linkage in their encoding, advanced methods such as linkage identification techniques and estimation of distribution algorithms work effectively although they need some additional computational cost. The computation time can be reduced by employing parallel computers and several approaches have been proposed for their parallelized algorithms. This paper presents empirical results on parallelization of the linkage identification compared to that of an estimation of distribution algorithm.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jiri, O.: Parallel Estimation of Distribution Algorithms. PhD thesis, Brno University of Technology (2002)
Munetomo, M., Goldberg, D.E.: Designing a genetic algorithm using the linkage identification by nonlinearity check. Technical Report IlliGAL Report No.98014, University of Illinois at Urbana-Champaign (1998)
Munetomo, M., Goldberg, D.E.: Identifying linkage by nonlinearity check. Technical Report IlliGAL Report No.98012, University of Illinois at Urbana- Champaign (1998)
Munetomo, M., Goldberg, D.E.: Identifying linkage groups by nonlinearity/non-monotonicity detection. In: Proceedings of the 1999 Genetic and Evolutionary Computation Conference (1999)
Munetomo, M., Murao, N., Akama, K.: A parallel genetic algorithm based on linkage identification. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2723, pp. 1222–1233. Springer, Heidelberg (2003)
Pelikan, M., Goldberg, D.E., Cantú-Paz, E.: BOA: The Bayesian optimization algorithm. IlliGAL Report No. 99003, Urbana, IL (1999)
Pelikan, M., Goldberg, D.E., Sastry, K.: Bayesian optimization algorithm, decision graphs, and occam’s razor. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001), pp. 519–526. Morgan Kaufmann, San Francisco (2001)
Goldberg, D.E., Deb, K., Korb, B.: Messy genetic algorithms revisited: Studies in mixed size and scale. Complex Systems 4, 415–444 (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Munetomo, M., Murao, N., Akama, K. (2004). Empirical Investigations on Parallelized Linkage Identification. In: Yao, X., et al. Parallel Problem Solving from Nature - PPSN VIII. PPSN 2004. Lecture Notes in Computer Science, vol 3242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30217-9_33
Download citation
DOI: https://doi.org/10.1007/978-3-540-30217-9_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23092-2
Online ISBN: 978-3-540-30217-9
eBook Packages: Springer Book Archive