Geometric Particle Swarm Optimization

Moraglio, Alberto; Di Chio, Cecilia; Togelius, Julian; Poli, Riccardo

doi:https://doi.org/10.1155/2008/143624

Journal of Artificial Evolution and Applications

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Particle Swarms: The Second Decade

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Research Article | Open Access

Volume 2008 | Article ID 143624 | https://doi.org/10.1155/2008/143624

Geometric Particle Swarm Optimization

Alberto Moraglio,¹Cecilia Di Chio,²Julian Togelius,³and Riccardo Poli²

Academic Editor: T. Blackwell

Received21 Jul 2007

Accepted04 Dec 2007

Published21 Feb 2008

Abstract

Using a geometric framework for the interpretation of crossover of recent introduction, we show an intimate connection between particle swarm optimisation (PSO) and evolutionary algorithms. This connection enables us to generalise PSO to virtually any solution representation in a natural and straightforward way. The new Geometric PSO (GPSO) applies naturally to both continuous and combinatorial spaces. We demonstrate this for the cases of Euclidean, Manhattan and Hamming spaces and report extensive experimental results. We also demonstrate the applicability of GPSO to more challenging combinatorial spaces. The Sudoku puzzle is a perfect candidate to test new algorithmic ideas because it is entertaining and instructive as well as being a nontrivial constrained combinatorial problem. We apply GPSO to solve the Sudoku puzzle.

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Copyright

Copyright © 2008 Alberto Moraglio et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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