Information Processing Letters
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
A theoretical and empirical analysis of convergence related particle swarm optimization
WSEAS Transactions on Systems and Control
Particle swarm optimization-based extremum seeking control
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
An empirical analysis of convergence related particle swarm optimization
MMACTEE'09 Proceedings of the 11th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
Swarm intelligence-based extremum seeking control
Expert Systems with Applications: An International Journal
Fuzzy decision support system for ship lock control
Expert Systems with Applications: An International Journal
Hi-index | 0.89 |
In this paper, a formal convergence analysis of the conventional PSO algorithms with time-varying parameters is presented. Based on this analysis, a new convergence-related parametric model for the conventional PSO is introduced. Finally, several new schemes for parameter adjustment, providing significant performance benefits, are introduced. Performance of these schemes is empirically compared to conventional PSO algorithms on a set of selected benchmarks. The tests prove effectiveness of the newly introduced schemes, especially regarding their ability to efficiently explore the search space.