Compound particle swarm optimization in dynamic environments.

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dc.contributor.authorLiu, Lilien
dc.contributor.authorWang, Dingweien
dc.contributor.authorYang, Shengxiangen
dc.date.accessioned2013-06-11T15:49:07Z
dc.date.available2013-06-11T15:49:07Z
dc.date.issued2008
dc.description.abstractAdaptation to dynamic optimization problems is currently receiving a growing interest as one of the most important applications of evolutionary algorithms. In this paper, a compound particle swarm optimization (CPSO) is proposed as a new variant of particle swarm optimization to enhance its performance in dynamic environments. Within CPSO, compound particles are constructed as a novel type of particles in the search space and their motions are integrated into the swarm. A special reflection scheme is introduced in order to explore the search space more comprehensively. Furthermore, some information preserving and anti-convergence strategies are also developed to improve the performance of CPSO in a new environment. An experimental study shows the efficiency of CPSO in dynamic environments.en
dc.identifier.citationLiu, L., Wang, D. and Yang, S. (2008) Compound particle swarm optimization in dynamic environments. In: ยป Applications of Evolutionary Computing: Proceedings of EvoWorkshops 2008: EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog, Naples, Italy, March 26-28, 2008. Berlin: Springer-Verlag, pp. 616-625.en
dc.identifier.doihttps://doi.org/10.1007/978-3-540-78761-7_67
dc.identifier.isbn978-3-540-78760-0
dc.identifier.urihttp://hdl.handle.net/2086/8724
dc.language.isoenen
dc.peerreviewedYesen
dc.publisherSpringer-Verlag.en
dc.relation.ispartofseriesLecture notes in computer science;Vol. 4974
dc.researchgroupCentre for Computational Intelligenceen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.titleCompound particle swarm optimization in dynamic environments.en
dc.typeArticleen

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