Publication | Closed Access
On the convergence analysis and parameter selection in particle swarm optimization
237
Citations
7
References
2004
Year
Unknown Venue
Numerical AnalysisEngineeringComputational MechanicsEvolutionary Multimodal OptimizationOperations ResearchSystems EngineeringHybrid Optimization TechniqueKinematicsApproximation TheoryConvergence AnalysisFirefly AlgorithmIntelligent OptimizationMechatronicsComputer EngineeringParticle Trajectory StudyComputer ScienceHybrid AlgorithmAerospace EngineeringParticle Swarm OptimizationParameter SelectionInertia WeightSole Empirical Study
A PSO with increasing inertia weight, distinct from a widely used PSO with decreasing inertia weight, is proposed in this paper. Far from drawing conclusions from sole empirical study or rule of thumb, this algorithm is derived from particle trajectory study and convergence analysis. Four standard test functions are used to confirm its validity finally. From the experiments, it is clear that a PSO with increasing inertia weight outperforms the one with decreasing inertia weight, both in convergent speed and solution precision, with no additional computing load.
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