SINGLE MACHINE SCHEDULING WITH GENERAL LEARNING FUNCTIONS: OPTIMAL SOLUTIONS

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dc.contributor.authorEren, Tamer
dc.date.accessioned2025-01-21T16:44:24Z
dc.date.available2025-01-21T16:44:24Z
dc.date.issued2013
dc.departmentKırıkkale Üniversitesi
dc.description.abstractIn traditional scheduling problems, most literature assumes that the processing time of a lob is fixed. However, there are many situations where the processing time of a job depends on the starting time or the position of the job in a sequence. In Such situations, the actual processing time of a job may be less than its normal processing time if it is scheduled later, This phenomenon is known as the learning effect. In this study, we introduce general learning functions into a single-machine scheduling problems. We consider the following objective functions: (i) sum of weighted completion times, (ii) maximum lateness (iii) number of tardy jobs (iv) number of weighted tardy jobs, Non-linear programming models are developed for solving these problems..
dc.identifier.doi10.5505/pajes.2013.43153
dc.identifier.endpage80
dc.identifier.issn1300-7009
dc.identifier.issn2147-5881
dc.identifier.issue2
dc.identifier.startpage76
dc.identifier.urihttps://doi.org/10.5505/pajes.2013.43153
dc.identifier.urihttps://hdl.handle.net/20.500.12587/25449
dc.identifier.volume19
dc.identifier.wosWOS:000443146600003
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isotr
dc.publisherPamukkale Univ
dc.relation.ispartofPamukkale University Journal of Engineering Sciences-Pamukkale Universitesi Muhendislik Bilimleri Dergisi
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjectSingle machine scheduling; Learning functions; Non-linear programming models
dc.titleSINGLE MACHINE SCHEDULING WITH GENERAL LEARNING FUNCTIONS: OPTIMAL SOLUTIONS
dc.typeArticle

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