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Pareto-based Self-Organizing Migrating Algorithm solving 100-Digit Challenge

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dc.title Pareto-based Self-Organizing Migrating Algorithm solving 100-Digit Challenge en
dc.contributor.author Truong, Thanh Cong
dc.contributor.author Diep, Quoc Bao
dc.contributor.author Zelinka, Ivan
dc.contributor.author Šenkeřík, Roman
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 13
dc.citation.epage 20
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_2
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-030-37838-7_2
dc.subject 100-digit challenge en
dc.subject optimization function en
dc.subject self-organizing migrating algorithm en
dc.subject SOMA Pareto en
dc.subject swarm intelligence en
dc.description.abstract In this article, we describe the design and implementation of a variant version of SOMA named SOMA Pareto to solve ten hard problems of the 100-Digit Challenge. The algorithm consists of the following operations: Organization, Migration, and Update. In which, we focus on improving the Organization operation with the adaptive parameters of PRT and Step. When applying the SOMA Pareto to solve ten hard problems to 10 digits of accuracy, we achieved a competitive result: 85.04 points. © Springer Nature Switzerland AG 2020. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1009559
utb.identifier.obdid 43881277
utb.identifier.scopus 2-s2.0-85078491635
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.fulltext.affiliation Thanh Cong Truong 1, Quoc Bao Diep 1, Ivan Zelinka 1, Roman Senkerik 2 1 Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava-Poruba, Ostrava, Czech Republic {cong.thanh.truong.st,ivan.zelinka}@vsb.cz, [email protected] 2 Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, 760 01 Zlin, Czech Republic [email protected]
utb.fulltext.dates -
utb.fulltext.sponsorship The following grants are acknowledged for the financial support provided for this research: Grant of SGS No. SP2019/137, VSB Technical University of Ostrava. This work was also 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.
utb.scopus.affiliation Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. listopadu 2172/15, Ostrava-Poruba, Ostrava, 708 00, Czech Republic; Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, Zlin, 760 01, Czech Republic
utb.fulltext.projects SP2019/137
utb.fulltext.projects LO1303
utb.fulltext.projects MSMT-7778/2014
utb.fulltext.projects CZ.1.05/2.1.00/03.0089
utb.fulltext.faculty Faculty of Applied Informatics
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