Publicação
A genetic approach to dynamic scheduling for total weighted tardiness problem
| datacite.subject.fos | Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática | |
| datacite.subject.sdg | 09:Indústria, Inovação e Infraestruturas | |
| dc.contributor.author | Madureira, Ana Maria | |
| dc.contributor.author | Ramos, Carlos | |
| dc.contributor.author | Silva, Sílvio do Carmo | |
| dc.contributor.editor | Petley, Gary | |
| dc.contributor.editor | Coddington, Alexandra | |
| dc.contributor.editor | Aylett, Ruth | |
| dc.date.accessioned | 2026-05-06T14:19:07Z | |
| dc.date.available | 2026-05-06T14:19:07Z | |
| dc.date.issued | 1999-12-15 | |
| dc.description.abstract | This paper presents several local search metaheuristics for the problem of scheduling a single machine to minimise total weighted tardiness. A genetic algorithm for the static single machine total weighted tardiness problem is presented, and a multistart version named metaGA is proposed. The obtained computational results permit to conclude about their efficiency and effectiveness. The resolution of the dynamic single machine total weighted tardiness problem using a scheduling system based on Genetic Algorithms (GA) is proposed. This approach extends the resolution of static Single Machine Scheduling Problems (SMSP) to dynamic SMSP in which changes can occur continually. A new population generating mechanism for dynamic environments is proposed. This method takes into account dynamic occurrences in a system, and adapts the current modified population into a new regenerated population. | eng |
| dc.identifier.citation | Madureira, A., Ramos, C. & Silva, S. C. (1999, December 15-16). A genetic approach to dynamic scheduling for total weighted tardiness problem. In Petley, G., Coddington, A. & Aylett, R. (Eds). Proceedings of the Eighteenth Workshop of the UK Planning and Scheduling Special Interest Group. (pp.100-108). University of Salford, UK. | |
| dc.identifier.issn | 1368-5708 | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/32338 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | University of Salford | |
| dc.rights.uri | N/A | |
| dc.subject | Scheduling | |
| dc.subject | dynamic scheduling | |
| dc.subject | metaheuristics | |
| dc.subject | genetic algorithms | |
| dc.title | A genetic approach to dynamic scheduling for total weighted tardiness problem | eng |
| dc.type | conference paper | |
| dspace.entity.type | Publication | |
| oaire.citation.conferenceDate | 1999-12-15 | |
| oaire.citation.conferencePlace | University of Salford, UK | |
| oaire.citation.endPage | 108 | |
| oaire.citation.startPage | 100 | |
| oaire.citation.title | Eighteenth Workshop of the UK Planning and Scheduling Special Interest Group | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Madureira | |
| person.familyName | Ramos | |
| person.givenName | Ana Maria | |
| person.givenName | Carlos | |
| person.identifier.ciencia-id | 7F1D-5AF2-A101 | |
| person.identifier.ciencia-id | 1011-FAFC-AEBA | |
| person.identifier.orcid | 0000-0002-0264-4710 | |
| person.identifier.orcid | 0000-0002-5143-1711 | |
| person.identifier.rid | AAH-1056-2021 | |
| person.identifier.rid | K-7403-2014 | |
| person.identifier.scopus-author-id | 8634629500 | |
| person.identifier.scopus-author-id | 7201559105 | |
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