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Insight into adaptive differential evolution variants with unconventional randomization schemes

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dc.title Insight into adaptive differential evolution variants with unconventional randomization schemes en
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Viktorin, Adam
dc.contributor.author Kadavý, Tomáš
dc.contributor.author Pluháček, Michal
dc.contributor.author Zelinka, Ivan
dc.relation.ispartof Communications in Computer and Information Science
dc.identifier.issn 1865-0929 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-03-037837-0
dc.date.issued 2020
utb.relation.volume 1092 CCIS
dc.citation.spage 177
dc.citation.epage 188
dc.event.title 7th International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2019, and 5th International Conference on Fuzzy and Neural Computing, FANCCO 2019
dc.event.location Maribor
utb.event.state-en Slovenia
utb.event.state-cs Slovinsko
dc.event.sdate 2019-07-10
dc.event.edate 2019-07-12
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer
dc.identifier.doi 10.1007/978-3-030-37838-7_16
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-030-37838-7_16
dc.subject CEC 2015 benchmark en
dc.subject chaos-driven heuristics en
dc.subject differential evolution en
dc.subject population diversity en
dc.description.abstract The focus of this work is the deeper insight into arising serious research questions connected with the growing popularity of combining metaheuristic algorithms and chaotic sequences showing quasi-periodic patterns. This paper reports an analysis of population dynamics by linking three elements like distribution of the results, population diversity, and differences between strategies of Differential Evolution (DE). Experiments utilize two frequently studied self-adaptive DE versions, which are simpler jDE and SHADE, further an original DE variant for comparisons, and totally ten chaos-driven quasi-random schemes for the indices selection in the DE. All important performance characteristics and population diversity are recorded and analyzed for the CEC 2015 benchmark set in 30D. © Springer Nature Switzerland AG 2020. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1009561
utb.identifier.obdid 43881279
utb.identifier.scopus 2-s2.0-85078406208
utb.source d-scopus
dc.date.accessioned 2020-02-11T10:07:40Z
dc.date.available 2020-02-11T10:07:40Z
utb.ou CEBIA-Tech
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Viktorin, Adam
utb.contributor.internalauthor Kadavý, Tomáš
utb.contributor.internalauthor Pluháček, Michal
utb.fulltext.affiliation Roman Senkerik1, Adam Viktorin 1, Tomas Kadavy 1, Michal Pluhacek 1, Ivan Zelinka 2 1 Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, 760 01 Zlin, Czech Republic senkerik@utb.cz 2 Faculty of Electrical Engineering and Computer Science, Technical University of Ostrava, 17. listopadu 15, Ostrava, Czech Republic ivan.zelinka@vsb.cz
utb.fulltext.dates -
utb.fulltext.sponsorship Authors RS, AV, TK and MP acknowledge the support of project No. LO1303 (MSMT-7778/2014) by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme, further the project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089 under the European Regional Development Fund. Authors AV and TK also acknowledge the Internal Grant Agency of Tomas Bata University under the project No. IGA/CebiaTech/2019/002. This work is also based upon support by COST Action CA15140 (ImAppNIO), and the resources of A.I.Lab at the Faculty of Applied Informatics, TBU in Zlin (ailab.fai.utb.cz). Finally, Author Ivan Zelinka acknowledges the support of grant SGS 2019/137, VSB-Technical University of Ostrava.
utb.scopus.affiliation Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, Zlin, 760 01, Czech Republic; Faculty of Electrical Engineering and Computer Science, Technical University of Ostrava, 17. listopadu 15, Ostrava, 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/2019/002
utb.fulltext.projects CA15140
utb.fulltext.projects ImAppNIO
utb.fulltext.projects SGS 2019/137
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Applied Informatics
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