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Heuristic algorithm for lot sizing and scheduling on identical parallel machines

creativeworkseries.issn1896-8325
dc.contributor.authorKsiążek, Roger
dc.date.available2024-04-26T07:48:24Z
dc.date.issued2022
dc.description.abstractThis paper presents a new heuristic algorithm for the task of lot sizing and scheduling for identical parallel machines. The new algorithm is based on the rolling-horizon approach and the fix-and-relax decomposition technique. Two variants of the algorithm are finally proposed for solving the problem of lot scheduling with parallel machines where the number of products and machines is greater than that of the machines. A computational experiment has been conducted for a group of 30 data sets. The results showed that the new algorithm efficiently provided good solutions for tasks with large numbers of machines and products.en
dc.description.placeOfPublicationKraków
dc.description.versionwersja wydawnicza
dc.identifier.doihttps://doi.org/10.7494/dmms.2022.16.4105
dc.identifier.eissn2300-7090
dc.identifier.issn1896-8325
dc.identifier.urihttps://repo.agh.edu.pl/handle/AGH/108060
dc.language.isoeng
dc.publisherWydawnictwa AGH
dc.relation.ispartofDecision Making in Manufacturing and Services
dc.rightsAttribution 4.0 International
dc.rights.accessotwarty dostęp
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/legalcode
dc.subjectlot sizingen
dc.subjectlot schedulingen
dc.subjectidentical parallel machinesen
dc.subjectheuristicsen
dc.subjectalgorithmen
dc.titleHeuristic algorithm for lot sizing and scheduling on identical parallel machinesen
dc.title.relatedDecision Making in Manufacturing and Services
dc.typeartykuł
dspace.entity.typePublication
publicationissue.paginationpp. 47-65
publicationvolume.volumeNumberVol. 16
relation.isAuthorOfPublication22c73683-e5d4-44d3-ae89-426f5a7f2b0e
relation.isAuthorOfPublication.latestForDiscovery22c73683-e5d4-44d3-ae89-426f5a7f2b0e
relation.isJournalOfPublication1a0d5e63-ca5d-4f88-98aa-28b13ec72c08
relation.isJournalVolumeOfPublication15008472-61cb-4b6b-8a94-3cd6dc8123a7
relation.isJournalVolumeOfPublication.latestForDiscovery15008472-61cb-4b6b-8a94-3cd6dc8123a7

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