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. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Moraglio, A., Di Chio, C., & Poli, R. (2007). Geometric particle swarm optimisation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4445 LNCS, pp. 125–136). Springer Verlag. https://doi.org/10.1007/978-3-540-71605-1_12
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