Publication | Closed Access
A Convergence Proof for the Particle Swarm Optimiser
137
Citations
20
References
2010
Year
Particle Swarm OptimiserGlobal ConvergenceEngineeringContinuous OptimizationStochastic OptimizationFirefly AlgorithmIntelligent OptimizationStochastic Diffusion SearchHybrid Optimization TechniquePso AlgorithmConvergence ProofApproximation TheoryConvergence AnalysisEvolutionary ProgrammingOperations Research
The Particle Swarm Optimiser (PSO) is a population based stochastic optimisation algorithm, empirically shown to be efficient and robust. This paper provides a proof to show that the original PSO does not have guaranteed convergence to a local optimum. A flaw in the original PSO is identified which causes stagnation of the swarm. Correction of this flaw results in a PSO algorithm with guaranteed convergence to a local minimum. Further extensions with provable global convergence are also described. Experimental results are provided to elucidate the behavior of the modified PSO as well as PSO variations with global convergence.
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