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DANTE - The combination between an ant colony optimization algorithm and a depth search method

2008Conference object Open access
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dc.contributor.authorCardoso, Pedro J. S.
dc.contributor.authorJesus, Mário
dc.contributor.authorMarquez, Alberto
dc.date.accessioned2015-11-30T15:44:04Z
dc.date.available2015-11-30T15:44:04Z
dc.date.issued2008
dc.description.abstractThe ε-DANTE method is an hybrid meta-heuristic. In combines the evolutionary Ant Colony Optimization (ACO) algorithms with a limited Depth Search. This Depth Search is based in the pheromone trails used by the ACO, which allows it to be oriented to the more promising areas of the search space. Some results are presented for the multiple objective k-Degree Spanning Trees problem, proving the effectiveness of the method when compared with other already tested evolutionary methods. © 2008 IEEE.
dc.identifier.doihttps://dx.doi.org/10.1109/HIS.2008.115
dc.identifier.isbn978-0-7695-3326-1
dc.identifier.otherAUT: MJE00980; PCA01382;
dc.identifier.urihttp://hdl.handle.net/10400.1/7228
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE
dc.relation.isbasedonP-007-NSJ
dc.subjectAnt colony optimization
dc.subjectHybrid meta-heuristic
dc.subjectMultiple objective optimization
dc.titleDANTE - The combination between an ant colony optimization algorithm and a depth search method
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceBarcelona, Espanha
oaire.citation.endPage41
oaire.citation.startPage36
oaire.citation.titleProceedings - 8th International Conference on Hybrid Intelligent Systems, HIS 2008
oaire.citation.title8th International Conference on Hybrid Intelligent Systems, HIS 2008
person.familyNameCardoso
person.familyNameJesus
person.givenNamePedro
person.givenNameMário
person.identifierR-000-CVV
person.identifier.ciencia-id5F10-1C37-FE45
person.identifier.orcid0000-0003-4803-7964
person.identifier.orcid0000-0001-9977-0491
person.identifier.ridG-6405-2013
person.identifier.scopus-author-id35602693500
person.identifier.scopus-author-id57194224499
rcaap.rightsopenAccess
rcaap.typeconferenceObject
relation.isAuthorOfPublication62bebc54-51ee-4e35-bcf5-6dd69efd09e0
relation.isAuthorOfPublication3fc4f551-ed35-4ba7-882b-481b4024761b
relation.isAuthorOfPublication.latestForDiscovery62bebc54-51ee-4e35-bcf5-6dd69efd09e0

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