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Hybrid population-based incremental learning to assign terminals to concentrators

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datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
datacite.subject.fosCiências Naturais::Matemáticas
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
dc.contributor.authorBernardino, Eugénia Moreira
dc.contributor.authorBernardino, Anabela Moreira
dc.contributor.authorSánchez-Pérez, Juan Manuel
dc.contributor.authorGómez-Pulido, Juan Antonio
dc.contributor.authorVega-Rodríguez, Miguel Angel
dc.date.accessioned2025-11-04T12:47:46Z
dc.date.available2025-11-04T12:47:46Z
dc.date.issued2010
dc.descriptionConference name - International Conference on Evolutionary Computation, ICEC 2010; Conference date - 24 October 2010 - 26 October 2010; Conference code - 83493
dc.descriptionFonte: https://www.scitepress.org/papers/2010/30763/30763.pdf
dc.description.abstractIn the last decade, we have seen a significant growth in communication networks. In centralised communication networks, a central computer serves several terminals or workstations. In large networks, some concentrators are used to increase the network efficiency. A collection of terminals is connected to a concentrator and each concentrator is connected to the central computer. In this paper we propose a Hybrid Population-based Incremental Learning (HPBIL) to assign terminals to concentrators. We use this algorithm to determine the minimum cost to form a network by connecting a given collection of terminals to a given collection of concentrators. We show that HPBIL is able to achieve good solutions, improving the results obtained by previous approaches.eng
dc.identifier.citationBernardino, E. M., Bernardino, A. M., Sánchez-Pérez, J. M., Pulido, J. A. G., & Rodríguez, M. Á. V. (2010, October). Hybrid Population-based Incremental Learning to Assign Terminals to Concentrators. In IJCCI (ICEC) (pp. 182-189). DOI: https://doi.org/10.5220/0003076301820189.
dc.identifier.doi10.5220/0003076301820189
dc.identifier.isbn978-989-8425-31-7
dc.identifier.urihttp://hdl.handle.net/10400.8/14489
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSciTePress - Science and and Technology Publications
dc.relation.hasversionhttps://ecta.scitevents.org/ICEC2010/home.asp
dc.relation.ispartofProceedings of the International Conference on Evolutionary Computation
dc.rights.uriN/A
dc.subjectCommunication networks
dc.subjectTerminal assignment problem
dc.subjectOptimisation algorithms
dc.subjectPopulation-based incremental learning
dc.titleHybrid population-based incremental learning to assign terminals to concentratorseng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2010-10
oaire.citation.conferencePlaceValencia, Spain
oaire.citation.endPage189
oaire.citation.startPage182
oaire.citation.titleICEC 2010 - Proceedings of the International Conference on Evolutionary Computation
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameBernardino
person.familyNameMoreira Bernardino
person.givenNameEugénia
person.givenNameAnabela
person.identifier.ciencia-id9616-F1BC-D8BD
person.identifier.ciencia-id081E-F3B8-316A
person.identifier.orcid0000-0001-5301-5853
person.identifier.orcid0000-0002-6561-5730
person.identifier.scopus-author-id24402754700
relation.isAuthorOfPublication893cf15c-eff8-4e43-949c-c1de6eb87599
relation.isAuthorOfPublication375ebe15-f84c-46a4-a3d9-6e4935a92187
relation.isAuthorOfPublication.latestForDiscovery893cf15c-eff8-4e43-949c-c1de6eb87599

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In the last decade, we have seen a significant growth in communication networks. In centralised communication networks, a central computer serves several terminals or workstations. In large networks, some concentrators are used to increase the network efficiency. A collection of terminals is connected to a concentrator and each concentrator is connected to the central computer. In this paper we propose a Hybrid Population-based Incremental Learning (HPBIL) to assign terminals to concentrators. We use this algorithm to determine the minimum cost to form a network by connecting a given collection of terminals to a given collection of concentrators. We show that HPBIL is able to achieve good solutions, improving the results obtained by previous approaches.
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