Abstract
Using a geometric framework for the interpretation of crossover of recent introduction, we show an intimate connection between particle swarm optimization (PSO) and evolutionary algorithms. This connection enables us to generalize PSO to virtually any solution representation in a natural and straightforward way. We demonstrate this for the cases of Euclidean, Manhattan and Hamming spaces.
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
Bäck, T., Fogel, D.B., Michalewicz, T.: Evolutionary Computation 1: Basic Algorithms and Operators. Institute of Physics Publishing (2000)
Deza, M., Laurent, M.: Geometry of cuts and metrics. Springer, Heidelberg (1991)
Jones, T.: Evolutionary Algorithms, Fitness Landscapes and Search. PhD thesis, University of New Mexico (1995)
Kennedy, J., Eberhart, R.C.: A Discrete Binary Version of the Particle Swarm Algorithm. IEEE, New York (1997)
Kennedy, J., Eberhart, R.C.: Swarm Intelligence. Morgan Kaufmann, San Francisco (2001)
Luke, S., Spector, L.: A Revised Comparison of Crossover and Mutation in Genetic Programming. In: Proceedings of Genetic Programming Conference (1998)
Moraglio, A., Poli, R.: Topological interpretation of crossover. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1377–1388 (2004)
Moraglio, A., Poli, R.: Topological crossover for the permutation representation. In: GECCO 2005 Workshop on Theory of Representations (2005)
Moraglio, A., Poli, R.: Product Geometric Crossover. In: Proceedings of the Parallel Problem Solving from Nature Conference, pp. 1018–1027 (2006)
Moraglio, A., Poli, R.: Geometric Crossover for Sets, Multisets and Partitions. In: Proceedings of the Parallel Problem Solving from Nature Conference, pp. 1038–1047 (2006)
Moraglio, A., Poli, R.: Geometric Landscape of Homologous Crossover for Syntactic Trees. In: Proceedings of the 2005 IEEE Congress on Evolutionary Computation, pp. 427–434. IEEE Computer Society Press, Los Alamitos (2005)
Moraglio, A., Poli, R., Seehuus, R.: Geometric crossover for biological sequences. In: Proc. of European Conference on Genetic Programming, pp. 121–132 (2006)
Pardalos, P.M., Resende, M.G.C.: Handbook of Applied Optimization. Oxford University Press, Oxford (2002)
Radcliffe, N.: Equivalence Class Analysis of Genetic Algorithms. Journal of Complex Systems 5, 183–205 (1991)
Van de Vel, M.L.J.: Theory of Convex Structures. North-Holland, Amsterdam (1993)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Moraglio, A., Di Chio, C., Poli, R. (2007). Geometric Particle Swarm Optimisation. In: Ebner, M., O’Neill, M., Ekárt, A., Vanneschi, L., Esparcia-Alcázar, A.I. (eds) Genetic Programming. EuroGP 2007. Lecture Notes in Computer Science, vol 4445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71605-1_12
Download citation
DOI: https://doi.org/10.1007/978-3-540-71605-1_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71602-0
Online ISBN: 978-3-540-71605-1
eBook Packages: Computer ScienceComputer Science (R0)