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Self-Organizing Migrating Algorithm with non-binary perturbation

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dc.title Self-Organizing Migrating Algorithm with non-binary perturbation en
dc.contributor.author Pluháček, Michal
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Viktorin, Adam
dc.contributor.author Kadavý, Tomáš
dc.relation.ispartof Communications in Computer and Information Science
dc.identifier.issn 1865-0929 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 9783030378370
dc.date.issued 2020
utb.relation.volume 1092 CCIS
dc.citation.spage 43
dc.citation.epage 57
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_5
dc.relation.uri https://link.springer.com/chapter/10.1007%2F978-3-030-37838-7_5
dc.subject Perturbation en
dc.subject Repulsivity en
dc.subject Self-organizing migrating algorithm en
dc.subject SOMA en
dc.description.abstract The self-organizing migrating algorithm (SOMA) is a popular population base metaheuristic. One of its key mechanisms is a perturbation of the individual movement with a binary-valued perturbation (PRT) vector. The goal of perturbation is to improve the diversity of the population and exploration of the search space. In this paper, we study a variant of the SOMA algorithm with non-binary PRT vector. We investigate the effect of introducing a third possible value, a negative (repulsive) element, into the PRT vector. The aim is to slow the population convergence and prolong the exploration phase. The inspiration is taken from previous successful implementations of repulsive mechanics in another swarm-based method: the Particle Swarm Optimization. © Springer Nature Switzerland AG 2020. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1009557
utb.identifier.obdid 43881276
utb.identifier.scopus 2-s2.0-85078415653
utb.source d-scopus
dc.date.accessioned 2020-02-11T10:07:39Z
dc.date.available 2020-02-11T10:07:39Z
utb.ou CEBIA-Tech
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Viktorin, Adam
utb.contributor.internalauthor Kadavý, Tomáš
utb.fulltext.affiliation Michal Pluhacek, Roman Senkerik, Adam Viktorin, Tomas Kadavy Faculty of Applied Informatics, Tomas Bata University in Zlin, Nam T.G. Masaryka 5555, 760 01 Zlin, Czech Republic {pluhacek,senkerik,aviktorin,kadavy}@utb.cz
utb.fulltext.dates -
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/2019/002. 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, Nam 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/2019/002
utb.fulltext.projects CA15140
utb.fulltext.projects ImAppNIO
utb.fulltext.projects IC1406
utb.fulltext.projects cHiPSet
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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