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dc.contributor.authorLacroix, Benjamin
dc.contributor.authorMolina, Daniel
dc.contributor.authorHerrera, Francisco
dc.date.accessioned2016-06-07T10:39:32Z
dc.date.available2016-06-07T10:39:32Z
dc.date.issued2016-06-02
dc.identifier.citationLACROIX, B., MOLINA, D. and HERRERA, F. 2016. Region-based memetic algorithm with archive for multimodal optimsation. Information sciences [online], 367-368, pages 719-746. Available from: https://dx.doi.org/10.1016/j.ins.2016.05.049en
dc.identifier.issn0020-0255en
dc.identifier.urihttp://hdl.handle.net/10059/1510
dc.description.abstractIn this paper we propose a specially designed memetic algorithm for multimodal optimisation problems. The proposal uses a niching strategy, called region-based niching strategy, that divides the search space in predefined and indexable hypercubes with decreasing size, called regions. This niching technique allows our proposal to keep high diversity in the population, and to keep the most promising regions in an external archive. The most promising solutions are improved with a local search method and also stored in the archive. The archive is used as an index to effiently prevent further exploration of these areas with the evolutionary algorithm. The resulting algorithm, called Region-based Memetic Algorithm with Archive, is tested on the benchmark proposed in the special session and competition on niching methods for multimodal function optimisation of the Congress on Evolutionary Computation in 2013. The results obtained show that the region-based niching strategy is more efficient than the classical niching strategy called clearing and that the use of the archive as restrictive index significantly improves the exploration efficiency of the algorithm. The proposal achieves better exploration and accuracy than other existing techniques.en
dc.description.sponsorshipSpanish Ministry of Education and Science under Grants TIN2012-37930-C02-01, TIN2014-57251-P, TIN2013-47210-P and Research Regional Projects P10-TIC-6858, P12-TIC-2958.en
dc.language.isoenen
dc.publisherElsevieren
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0en
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMultimodal optimisationen
dc.subjectMemetic algorithmen
dc.subjectNiching strategyen
dc.titleRegion-based memetic algorithm with archive for multimodal optimsation.en
dc.typeJournal articlesen
dc.publisher.urihttps://dx.doi.org/10.1016/j.ins.2016.05.049en
dcterms.dateAccepted2016-05-29
refterms.accessExceptionNAen
refterms.dateDeposit2016-06-07
refterms.dateEmbargoEnd2017-06-02
refterms.dateFCA2017-06-02
refterms.dateFreeToDownload2017-06-02
refterms.dateFreeToRead2017-06-02
refterms.dateToSearch2017-06-02
refterms.depositExceptionNAen
refterms.panelBen
refterms.technicalExceptionNAen
refterms.versionAMen
rioxxterms.publicationdate2016-06-02
rioxxterms.typeJournal Article/Reviewen


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