EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
The particle swarm optimization algorithm: convergence analysis and parameter selection
Information Processing Letters
Particle swarms and population diversity
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Fundamentals of Computational Swarm Intelligence
Fundamentals of Computational Swarm Intelligence
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Proceedings of the 9th annual conference on Genetic and evolutionary computation
FOGA'07 Proceedings of the 9th international conference on Foundations of genetic algorithms
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Stability analysis of the particle dynamics in particle swarm optimizer
IEEE Transactions on Evolutionary Computation
Convergence behavior of the fully informed particle swarm optimization algorithm
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Allocation of local and global search capabilities of particle in canonical PSO
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Frankenstein's PSO: a composite particle swarm optimization algorithm
IEEE Transactions on Evolutionary Computation
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A method is presented that allows one to exactly determine all the characteristics of a PSO's sampling distribution and explain how it changes over time, in the presence stochasticity. The only assumption made is stagnation (particles are in search for a better personal best).