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Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/803
DC FieldValueLanguage
dc.contributor.authorMilanović, M.en_US
dc.contributor.authorMatić, D.en_US
dc.contributor.authorSavić, Aleksandaren_US
dc.contributor.authorKratica, J.en_US
dc.date.accessioned2022-08-15T15:47:45Z-
dc.date.available2022-08-15T15:47:45Z-
dc.date.issued2011-07-15-
dc.identifier.issn16833511en
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/803-
dc.description.abstractTwo metaheuristic methods for solving the p-ary transitive reduction (TRP) problem are proposed: a genetic algorithm and a reduced variable neighborhood search method. Experiments were performed on a set of randomly generated instances. Presented results are the first experimental results in the literature so far for values p > 2.en_US
dc.language.isoenen_US
dc.publisherInstitute of Applied Mathematics of Baku State Universityen_US
dc.relation.ispartofApplied and Computational Mathematicsen_US
dc.subjectEvolutionary Algorithmen_US
dc.subjectSignal Transduction Networksen_US
dc.subjectSystems Biologyen_US
dc.subjectTransitive Reductionen_US
dc.subjectVariable Neighborhood Searchen_US
dc.titleTwo metaheuristic approaches to solving the p-ary transitive reduction problemen_US
dc.typeArticleen_US
dc.identifier.scopus2-s2.0-79960162664-
dc.identifier.isi000292437000008-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/79960162664-
dc.contributor.affiliationNumerical Mathematics and Optimizationen_US
dc.relation.issn1683-3511en_US
dc.description.rankM22en_US
dc.relation.firstpage294en_US
dc.relation.lastpage308en_US
dc.relation.volume10en_US
dc.relation.issue2en_US
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
crisitem.author.deptNumerical Mathematics and Optimization-
crisitem.author.orcid0009-0003-8568-4260-
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