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Regarding the behavior of bison runners within the Bison algorithm

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dc.title Regarding the behavior of bison runners within the Bison algorithm en
dc.contributor.author Kazíková, Anežka
dc.contributor.author Pluháček, Michal
dc.contributor.author Šenkeřík, Roman
dc.relation.ispartof Mendel
dc.identifier.issn 1803-3814 OCLC, Ulrich, Sherpa/RoMEO, JCR
dc.date.issued 2018
utb.relation.volume 24
utb.relation.issue 1
dc.citation.spage 63
dc.citation.epage 70
dc.type article
dc.language.iso en
dc.publisher Brno University of Technology
dc.identifier.doi 10.13164/mendel.2018.1.063
dc.relation.uri https://mendel-journal.org/index.php/mendel/article/view/24
dc.subject Bison algorithm en
dc.subject Bison seeker algorithm en
dc.subject Optimization en
dc.subject Swarm algorithms en
dc.description.abstract This paper proposes a modification of the Bison Algorithm’s running technique, which allows the running group to exploit the areas of discovered promising solutions. It also provides a closer examination of the successful running behavior and its impact on the overall optimization process. The new algorithm is then compared to other optimization algorithms on the IEEE CEC 2017 benchmark solving continuous minimization problems. © 2018, Brno University of Technology. All rights reserved. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1009091
utb.identifier.scopus 2-s2.0-85066326306
utb.source j-scopus
dc.date.accessioned 2019-09-19T07:56:16Z
dc.date.available 2019-09-19T07:56:16Z
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.ou CEBIA-Tech
utb.contributor.internalauthor Kazíková, Anežka
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Šenkeřík, Roman
utb.fulltext.sponsorship This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014), further 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 Projects no. IGA/CebiaTech/2018/003. This work is also based upon support by COST (European Cooperation in Science & Technology) under Action CA15140, Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice (ImAppNIO), and Action IC1406, High-Performance Modelling and Simulation for Big Data Applications (cHiPSet). 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, T.G.Masaryka 5555, Zlin, 760 01, Czech Republic
utb.fulltext.projects LO1303
utb.fulltext.projects MSMT-7778/2014
utb.fulltext.projects CZ.1.05/2.1.00/03.0089
utb.fulltext.projects IGA/CebiaTech/2018/003
utb.fulltext.projects CA15140
utb.fulltext.projects IC1406
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