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Relation of neighborhood size and diversity loss rate in particle swarm optimization with ring topology

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dc.title Relation of neighborhood size and diversity loss rate in particle swarm optimization with ring topology en
dc.contributor.author Pluháček, Michal
dc.contributor.author Kazíková, Anežka
dc.contributor.author Kadavý, Tomáš
dc.contributor.author Viktorin, Adam
dc.contributor.author Šenkeřík, Roman
dc.relation.ispartof Mendel
dc.identifier.issn 1803-3814 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2021
utb.relation.volume 27
utb.relation.issue 2
dc.citation.spage 74
dc.citation.epage 79
dc.type article
dc.language.iso en
dc.publisher Brno University of Technology
dc.identifier.doi 10.13164/mendel.2021.2.074
dc.relation.uri https://mendel-journal.org/index.php/mendel/article/view/151/162
dc.subject LPSO en
dc.subject neighborhood en
dc.subject Particle Swarm Optimization en
dc.subject population diversity en
dc.subject ring topology en
dc.description.abstract Measuring the population diversity in metaheuristics has become a common practice for adaptive approaches, aiming mainly to address the issue of premature convergence. Understanding the processes leading to a diversity loss in a metaheuristic algorithm is crucial for designing successful adaptive approaches. In this study, we focus on the relation of the neighborhood size and the rate of diversity loss in the Particle Swarm Optimization algorithm with local topology (also known as LPSO). We argue that the neighborhood size is an important input to consider when designing any adaptive approach based on the change of population diversity. We used the extensive benchmark suite of the IEEE CEC 2014 competition for experiments. © 2021, Brno University of Technology. All rights reserved. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1010816
utb.identifier.obdid 43883340
utb.identifier.scopus 2-s2.0-85123621688
utb.source j-scopus
dc.date.accessioned 2022-02-07T11:18:21Z
dc.date.available 2022-02-07T11:18:21Z
dc.description.sponsorship Univerzita Tomáše Bati ve Zlíně: IGA/CebiaTech/2021/001
dc.rights Attribution-NonCommercial-ShareAlike 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Kazíková, Anežka
utb.contributor.internalauthor Kadavý, Tomáš
utb.contributor.internalauthor Viktorin, Adam
utb.contributor.internalauthor Šenkeřík, Roman
utb.fulltext.affiliation Michal Pluhacek✉, Anezka Kazikova, Tomas Kadavy, Adam Viktorin, Roman Senkerik Faculty of Applied Informatics, Tomas Bata University in Zlin, Zlin, Czech Republic pluhacek@utb.cz ✉, kazikova@utb.cz, kadavy@utb.cz, aviktorin@utb.cz, senkerik@utb.cz
utb.fulltext.dates Received: 07 October 2021 Accepted: 15 December 2021 Published: 21 December 2021
utb.fulltext.sponsorship This work was supported by the Internal Grant Agency of Tomas Bata University under the Projects no. IGA/CebiaTech/2021/001. The work was further supported by resources of A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).
utb.scopus.affiliation Faculty of Applied Informatics, Tomas Bata University in Zlin, Zlin, Czech Republic
utb.fulltext.projects IGA/CebiaTech/2021/001
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.ou -
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