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A Genetic Algorithm for the Dynamic Single Machine Scheduling Problem

datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorSilva, Sílvio do Carmo
dc.contributor.authorMadureira, Ana Maria
dc.contributor.authorRamos, Carlos
dc.contributor.editorCamarinha-Matos, Luís
dc.contributor.editorAfsarmanesh, Hamideh
dc.contributor.editorErbe, Heinz-H.
dc.date.accessioned2026-03-31T08:00:22Z
dc.date.available2026-03-31T08:00:22Z
dc.date.issued2000
dc.description.abstractThis paper starts by studying the performance of two interrelated genetic algorithms (GA) for the static Single Machine Scheduling Problem (SMSP). One is a single start GA, the other, called MetaGA, is a multi-start version GA. The performance is evaluated for total weighted tardiness, on the basis of the quality of scheduling solutions obtained for a limit on computation time. Then, a scheduling system, based on Genetic Algorithms is proposed, for the resolution of the dynamic version of the same problem. The approach used adapts the resolution of the static problem to the dynamic one in which changes may occur continually. This takes into account dynamic occurrences in a system and adapts the current population to a new regenerated populationeng
dc.identifier.citationMadureira, A., Ramos, C., do Carmo Silva, S. (2000). A Genetic Algorithm for the Dynamic Single Machine Scheduling Problem. In: Camarinha-Matos, L.M., Afsarmanesh, H., Erbe, HH. (eds) Advances in Networked Enterprises. BASYS 2000. IFIP — The International Federation for Information Processing, vol 53. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35529-0_30
dc.identifier.doi10.1007/978-0-387-35529-0_30
dc.identifier.isbn0-7923-7958-6
dc.identifier.urihttp://hdl.handle.net/10400.22/32174
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-0-387-35529-0_30#Abs1
dc.rights.uriN/A
dc.titleA Genetic Algorithm for the Dynamic Single Machine Scheduling Problemeng
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferenceDate2000-09-29
oaire.citation.conferencePlaceBerlin, Germany
oaire.citation.endPage324
oaire.citation.startPage315
oaire.citation.titleAdvances in Networked Enterprises. BASYS 2000. IFIP — The International Federation for Information Processing
oaire.citation.volume53
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameMadureira
person.familyNameRamos
person.givenNameAna Maria
person.givenNameCarlos
person.identifier.ciencia-id7F1D-5AF2-A101
person.identifier.ciencia-id1011-FAFC-AEBA
person.identifier.orcid0000-0002-0264-4710
person.identifier.orcid0000-0002-5143-1711
person.identifier.ridAAH-1056-2021
person.identifier.ridK-7403-2014
person.identifier.scopus-author-id8634629500
person.identifier.scopus-author-id7201559105
relation.isAuthorOfPublicationcd5e5eb7-cf63-48c6-b6b9-a9db2fedebab
relation.isAuthorOfPublication43ef055e-80e6-4b31-8400-2d3592927e03
relation.isAuthorOfPublication.latestForDiscoverycd5e5eb7-cf63-48c6-b6b9-a9db2fedebab

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