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A Hybrid Population-Based Incremental Learning algorithm for load balancing in RPR

datacite.subject.fosEngenharia e Tecnologia::Engenharia Médica
datacite.subject.fosCiências Médicas::Ciências da Saúde
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
dc.contributor.authorBernardino, Anabela M.
dc.contributor.authorBernardino, Eugénia M.
dc.contributor.authorSánchez-Pérez, Juan Manuel
dc.contributor.authorGómez-Pulido, Juan Antonio
dc.contributor.authorVega-Rodríguez, Miguel Angel
dc.date.accessioned2025-12-02T12:39:30Z
dc.date.available2025-12-02T12:39:30Z
dc.date.issued2010-11
dc.descriptionEISBN - 978-1-4244-8132-3
dc.description.abstractWhen managed properly, the ring networks are uniquely suited to deliver a large amount of bandwidth in a reliable and inexpensive way. An optimal load balancing is very important, because it increases the system capacity and improves the overall ring performance. An important optimisation problem in this context is the Weighted Ring Arc Loading Problem (WRALP). It consists of the design, in a communication network of a transmission route (direct path) for each request, such that high load on the ring arcs will be avoided. WRALP asks for a routing scheme such that the maximum load on the ring arcs will be minimum. In this paper we study WRALP without demand splitting and we propose a Hybrid Populationbased Incremental Learning (HPBIL) to solve it. We show that HPBIL is able to achieve good solutions, improving the results obtained by previous approaches.eng
dc.identifier.citationA. M. Bernardino, E. M. Bernardino, J. M. Sánchez-Pérez, J. A. Gómez-Pulido and M. A. Vega-Rodríguez, "A Hybrid Population-Based Incremental Learning algorithm for load balancing in RPR," 2010 3rd International Symposium on Applied Sciences in Biomedical and Communication Technologies (ISABEL 2010), Rome, Italy, 2010, pp. 1-5, doi: https://doi.org/10.1109/ISABEL.2010.5702810.
dc.identifier.doi10.1109/isabel.2010.5702810
dc.identifier.eissn2325-5331
dc.identifier.isbn978-1-4244-8131-6
dc.identifier.isbn978-1-4244-8132-3
dc.identifier.issn2325-5315
dc.identifier.urihttp://hdl.handle.net/10400.8/14801
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE Canada
dc.relation.hasversionhttps://ieeexplore.ieee.org/document/5702810
dc.relation.ispartof2010 3rd International Symposium on Applied Sciences in Biomedical and Communication Technologies (ISABEL 2010)
dc.rights.uriN/A
dc.subjectCommunication Networks
dc.subjectOptimisation algorithms
dc.subjectWeighted Ring Arc-Loading Problem
dc.subjectPopulation-Based Incremental Learning
dc.titleA Hybrid Population-Based Incremental Learning algorithm for load balancing in RPReng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2010-11
oaire.citation.conferencePlaceRome, Italy
oaire.citation.title2010 3rd International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL 2010
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameMoreira Bernardino
person.familyNameBernardino
person.givenNameAnabela
person.givenNameEugénia
person.identifier.ciencia-id081E-F3B8-316A
person.identifier.ciencia-id9616-F1BC-D8BD
person.identifier.orcid0000-0002-6561-5730
person.identifier.orcid0000-0001-5301-5853
person.identifier.scopus-author-id24402754700
relation.isAuthorOfPublication375ebe15-f84c-46a4-a3d9-6e4935a92187
relation.isAuthorOfPublication893cf15c-eff8-4e43-949c-c1de6eb87599
relation.isAuthorOfPublication.latestForDiscovery375ebe15-f84c-46a4-a3d9-6e4935a92187

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When managed properly, the ring networks are uniquely suited to deliver a large amount of bandwidth in a reliable and inexpensive way. An optimal load balancing is very important, because it increases the system capacity and improves the overall ring performance. An important optimisation problem in this context is the Weighted Ring Arc Loading Problem (WRALP). It consists of the design, in a communication network of a transmission route (direct path) for each request, such that high load on the ring arcs will be avoided. WRALP asks for a routing scheme such that the maximum load on the ring arcs will be minimum. In this paper we study WRALP without demand splitting and we propose a Hybrid Populationbased Incremental Learning (HPBIL) to solve it. We show that HPBIL is able to achieve good solutions, improving the results obtained by previous approaches.
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