Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/678
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dc.contributor.authorKratica, Jozefen_US
dc.contributor.authorKojić, Jelenaen_US
dc.contributor.authorTošić, Dušanen_US
dc.contributor.authorFilipović, Vladimiren_US
dc.contributor.authorDugošija, Djordjeen_US
dc.date.accessioned2022-08-14T09:49:36Z-
dc.date.available2022-08-14T09:49:36Z-
dc.date.issued2009-01-01-
dc.identifier.isbn9783540896180-
dc.identifier.issn18675662en
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/678-
dc.description.abstractThe problem that we will address here is the Super-Peer Selection Problem (SPSP). Two hybrid genetic algorithm (HGA) approaches are proposed for solving this NP-hard problem. The new encoding schemes are implemented with appropriate objective functions. Both approaches keep the feasibility of individuals by using specific representation and modified genetic operators. The numerical experiments were carried out on the standard data set known from the literature. The results of this test show that in 6 out of 12 cases HGAs outreached best known solutions so far, and that our methods are competitive with other heuristics. © Springer-Verlag Berlin Heidelberg 2009.en
dc.relation.ispartofAdvances in Intelligent and Soft Computingen_US
dc.titleTwo hybrid genetic algorithms for solving the super-peer selection problemen_US
dc.typeConference Paperen_US
dc.relation.publicationApplications of Soft Computing, World Soft Computing (WSC) Conference 2008en_US
dc.identifier.doi10.1007/978-3-540-89619-7_33-
dc.identifier.scopus2-s2.0-84879311429-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84879311429-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.relation.firstpage337en_US
dc.relation.lastpage346en_US
dc.relation.volume58en_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairetypeConference Paper-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.orcid0000-0002-5943-8037-
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