Swarm intelligence
Topological crossover for the permutation representation
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Geometric particle swarm optimisation
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Geometric crossover for sets, multisets and partitions
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Geometric crossover for biological sequences
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Compound particle swarm optimization in dynamic environments
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Geometry of evolutionary algorithms
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Geometry of evolutionary algorithms
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
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Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of traditional particle swarm optimization (PSO) that applies naturally to both continuous and combinatorial spaces. In previous work we have developed the theory behind it. The aim of this paper is to demonstrate the applicability of GPSO in practice. We demonstrate this for the cases of Euclidean, Manhattan and Hamming spaces and report extensive experimental results.