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Complex network analysis in PSO as an fitness landscape classifier

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dc.title Complex network analysis in PSO as an fitness landscape classifier en
dc.contributor.author Pluháček, Michal
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Viktorin, Adam
dc.contributor.author Janoštík, Jakub
dc.contributor.author Davendra, Donald David
dc.relation.ispartof 2016 IEEE Congress on Evolutionary Computation, CEC 2016
dc.identifier.isbn 9781509006229
dc.date.issued 2016
dc.citation.spage 3332
dc.citation.epage 3337
dc.event.title 2016 IEEE Congress on Evolutionary Computation, CEC 2016
dc.event.location Vancouver
utb.event.state-en Canada
utb.event.state-cs Kanada
dc.event.sdate 2016-07-24
dc.event.edate 2016-07-29
dc.type conferenceObject
dc.language.iso en
dc.publisher Institute of Electrical and Electronics Engineers (IEEE)
dc.identifier.doi 10.1109/CEC.2016.7744211
dc.relation.uri http://ieeexplore.ieee.org/document/7744211/
dc.subject Complex network en
dc.subject Fitness landscape analysis en
dc.subject Particle swarm optimization en
dc.subject PSO en
dc.description.abstract In this paper, an initial small-scale study is carried out. It is proposed that using the complex network analysis it may be possible to make a classification of the fitness landscape type. A complex network is constructed from the inner dynamics of the population in PSO algorithm. The mean and maximal number of links in the network is then evaluated alongside with other basic statistic characteristics. It is shown on a basic function set that the number of links in the networks may vary significantly when facing unimodal and multimodal problems. Initial visualizations of the constructed complex networks are presented and the results are discussed with proposals for future research and possible future applications of this method. © 2016 IEEE. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1006961
utb.identifier.obdid 43876203
utb.identifier.scopus 2-s2.0-85008248837
utb.identifier.wok 000390749103067
utb.source d-wok
dc.date.accessioned 2017-07-13T14:50:27Z
dc.date.available 2017-07-13T14:50:27Z
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Viktorin, Adam
utb.contributor.internalauthor Janoštík, Jakub
utb.fulltext.affiliation Michal Pluhacek, Roman Senkerik, Adam Viktorin Jakub Janostik Faculty of Applied Informatics Tomas Bata University in Zlin T.G. Masaryka 5555, 760 01 Zlin, Czech Republic {pluhacek, senkerik, janostik,viktorin}@fai.utb.cz Donald Davendra Computer Science Department Central Washington University 400 E. University Way, Ellensburg, WA 98926-7520 USA. donaldd@cwu.edu
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by Grant Agency of the Czech Republic – GACR P103/15/06700S, further by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014. Also by the European Regional Development Fund under the Project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089 and by Internal Grant Agency of Tomas Bata University under the Project no. IGA/CebiaTech/2016/007.
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