The use of global best position in rerun of particle swarm optimization

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dc.contributor.authorCheypoca, Varothon
dc.contributor.authorSiriboon, Kritawan
dc.contributor.authorKruatrachue, Boontee
dc.date.accessioned2026-08-06T10:20:51Z
dc.date.available2026-08-06T10:20:51Z
dc.date.issued2018-08-13
dc.description.abstractThis paper studies the use of particle best position (GBEST) in rerun when particle swarm optimization (PSO) traps in local optima. Reinitialize particles positions are often used to restart PSO to get better results when trapping in local optima. This paper proposed the use of GBEST to further force particle movement out of previous local optima instead of only reset GBEST. The proposed method is tested on 26 benchmark test functions with satisfactory results.
dc.identifier.citationIceast 2018 4th International Conference on Engineering Applied Sciences and Technology Exploring Innovative Solutions for Smart Society, 2018
dc.identifier.doi10.1109/ICEAST.2018.8434504
dc.identifier.other2-s2.0-85053138001
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/8841
dc.sourceIceast 2018 4th International Conference on Engineering Applied Sciences and Technology Exploring Innovative Solutions for Smart Society
dc.subjectcomponent
dc.subjectGBEST
dc.subjectparticle swarm optimization
dc.subjectReinitialize
dc.titleThe use of global best position in rerun of particle swarm optimization
dc.typeConference Paper

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