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Erschienen in:
2006 | OriginalPaper | Buchkapitel
Particle Swarm Optimisation from lbest to gbest
verfasst von : Hongbo Liu, Bo Li, Ye Ji, Tong Sun
Erschienen in: Applied Soft Computing Technologies: The Challenge of Complexity
Verlag: Springer Berlin Heidelberg
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The effects of various neighborhood models on the particle swarm algorithm were investigated in this paper. We also gave some additional insight into the PSO neighborhood model selection topic. Our experiment results testified that the gbest model converges quickly on problem solutions but has a weakness for becoming trapped in local optima, while the lbest model converges slowly on problem solutions but is able to “flow around” local optima, as the individuals explore different regions. The gbest model is recommended strongly for unimodal objective functions, while a variable neighborhood model is recommended for multimodal objective functions.