Publication | Closed Access
The Standard Particle Swarm Optimization Algorithm Convergence Analysis and Parameter Selection
41
Citations
8
References
2007
Year
Unknown Venue
Numerical AnalysisOperations ResearchNonlinear System IdentificationEngineeringSmall Inertia WeightHybrid AlgorithmFirefly AlgorithmDiscrete Dynamical SystemIntelligent OptimizationParticle TrajectoriesSystems EngineeringFormal SufficientHybrid Optimization TechniqueModeling And SimulationComputational MechanicsParameter SelectionEvolutionary Multimodal OptimizationStability
Formal sufficient and necessary condition for the deterministic standard PSO algorithm to converge to equilibrium point, diverge to infinity or oscillate within a range is derived based on the discrete time dynamic system theory. General guidelines for parameters selection are provided according to the theory analysis. It is pointed out that, strictly speaking, the currently popular view that small inertia weight will facilitate a local search is not accurate enough. And the condition for the view to hold is given. The simulation results of particle trajectories are given to illustrate and verify the theory analysis.
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