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dc.contributor.authorPluháček, Michal
dc.contributor.authorViktorin, Adam
dc.contributor.authorŠenkeřík, Roman
dc.contributor.authorKadavý, Tomáš
dc.contributor.authorZelinka, Ivan
dc.date.accessioned2020-10-14T07:49:41Z
dc.date.available2020-10-14T07:49:41Z
dc.date.issued2020
dc.identifier.citationLogic Journal of the IGPL. 2020, vol. 28, issue 2, special issue, p. 211-225.cs
dc.identifier.issn1367-0751
dc.identifier.issn1368-9894
dc.identifier.urihttp://hdl.handle.net/10084/142310
dc.description.abstractThis extended study presents a hybridization of particle swarm optimization (PSO) with complex network construction and analysis. A partial population restart is performed in certain moments of the run of the algorithm based on the information obtained from a complex network analysis. The complex network structure represents the communication in the population. We present experimental results of the method alongside with statistical evaluation and discuss future possibilities of this approach. The main goal of the work is not to propose a new highly competitive PSO variant but to present the possibility of using the unconventional tool as an alternative to conventional diversity measures. The main benefit of the network analysis is that it has same-time requirements regardless of the dimension of the problem.cs
dc.language.isoencs
dc.publisherOxford University Presscs
dc.relation.ispartofseriesLogic Journal of the IGPLcs
dc.relation.urihttp://doi.org/10.1093/jigpal/jzy046cs
dc.rights© The Author(s) 2018. Published by Oxford University Press. All rights reserved.cs
dc.subjectswarm intelligencecs
dc.subjectparticle swarm optimizationcs
dc.subjectcomplex networkcs
dc.subjecthybrid methodcs
dc.titleExtended experimental study on PSO with partial population restart based on complex network analysiscs
dc.typearticlecs
dc.identifier.doi10.1093/jigpal/jzy046
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume28cs
dc.description.issue2cs
dc.description.lastpage225cs
dc.description.firstpage211cs
dc.identifier.wos000559006600006


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