Swarm intelligence
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Geometric particle swarm optimization for the sudoku puzzle
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Geometric particle swarm optimization
Journal of Artificial Evolution and Applications - Particle Swarms: The Second Decade
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 biological sequences
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
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 a simplified form of traditional particle swarm optimization (PSO) without the inertia term that applies naturally to both continuous and combinatorial spaces. In this paper, we propose an extension of GPSO, the inertial GPSO (IGPSO), that generalizes the traditional PSO endowed with the full equation of motion of particles to generic search spaces. We then formally derive the specific IGPSO for the Hamming space associated with binary strings and present experimental results for this new algorithm.