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On the adaptivity and complexity embedded into differential evolution

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dc.title On the adaptivity and complexity embedded into differential evolution en
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Pluháček, Michal
dc.contributor.author Zelinka, Ivan
dc.contributor.author Jašek, Roman
dc.relation.ispartof Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2015 (ICNAAM-2015)
dc.identifier.issn 0094-243X Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 9780735413924
dc.date.issued 2016
utb.relation.volume 1738
dc.event.title International Conference of Numerical Analysis and Applied Mathematics 2015, ICNAAM 2015
dc.event.location Rhodes
utb.event.state-en Greece
utb.event.state-cs Řecko
dc.event.sdate 2015-09-23
dc.event.edate 2015-09-29
dc.type conferenceObject
dc.language.iso en
dc.publisher American Institute of Physics (AIP)
dc.identifier.doi 10.1063/1.4951913
dc.relation.uri http://scitation.aip.org/content/aip/proceeding/aipcp/10.1063/1.4951913
dc.subject chaotic dynamics en
dc.subject discrete chaotic maps en
dc.subject evolutionary algorithms en
dc.subject Heuristic en
dc.description.abstract This research deals with the comparison of the two modern approaches for evolutionary algorithms, which are the adaptivity and complex chaotic dynamics. This paper aims on the investigations on the chaos-driven Differential Evolution (DE) concept. This paper is aimed at the embedding of discrete dissipative chaotic systems in the form of chaotic pseudo random number generators for the DE and comparing the influence to the performance with the state of the art adaptive representative jDE. This research is focused mainly on the possible disadvantages and advantages of both compared approaches. Repeated simulations for Lozi map driving chaotic systems were performed on the simple benchmark functions set, which are more close to the real optimization problems. Obtained results are compared with the canonical not-chaotic and not adaptive DE. Results show that with used simple test functions, the performance of ChaosDE is better in the most cases than jDE and Canonical DE, furthermore due to the unique sequencing in CPRNG given by the hidden chaotic dynamics, thus better and faster selection of unique individuals from population, ChaosDE is faster. © 2016 Author(s). en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1006665
utb.identifier.obdid 43876356
utb.identifier.scopus 2-s2.0-84984591100
utb.identifier.wok 000380803300159
utb.source d-scopus
dc.date.accessioned 2016-10-25T12:38:04Z
dc.date.available 2016-10-25T12:38:04Z
dc.rights.access openAccess
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Jašek, Roman
utb.fulltext.affiliation Roman Senkerik a, Michal Pluhacek a, Ivan Zelinka b and Roman Jasek a a Tomas Bata University in Zlin , Faculty of Applied Informatics, Nam T.G. Masaryka 5555, 760 01 Zlin, Czech Republic, {senkerik,pluhacek}@fai.utb.cz b Technical University of Ostrava, Faculty of Electrical Engineering and Computer Science, 17. listopadu 15,708 33 Ostrava-Poruba, Czech Republic, ivan.zelinka@vsb.cz
utb.fulltext.references -
utb.fulltext.sponsorship This work was supported by Grant Agency of the Czech Republic - GACR P103/15/06700S, further by financial support of research project NPU I No. MSMT-7778/2014 by the Ministry of Education of the Czech Republic and also by the European Regional Development Fund under the Project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089, partially supported by Grant of SGS No. SP2015/142 and SP2015/141 of VSB - Technical University of Ostrava, Czech Republic and by Internal Grant Agency of Tomas Bata University under the projects No. IGA/FAI/2015/057.
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