A genetic algorithm for the stochastic mixed-model U-line balancing and sequencing problem

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dc.contributor.authorOzcan, Ugur
dc.contributor.authorKellegoz, Talip
dc.contributor.authorToklu, Bilal
dc.date.accessioned2020-06-25T17:52:09Z
dc.date.available2020-06-25T17:52:09Z
dc.date.issued2011
dc.departmentKırıkkale Üniversitesi
dc.descriptionOZCAN, UGUR/0000-0001-8283-9579
dc.description.abstractMixed-model assembly lines are widely used to improve the flexibility to adapt to the changes in market demand, and U-lines have become popular in recent years as an important component of just-in-time production systems. As a consequence of adaptation of just-in-time production principles into the manufacturing environment, mixed-model production is performed on U-lines. This type of a production line is called a mixed-model U-line. In mixed-model U-lines, there are two interrelated problems called line balancing and model sequencing. In real life applications, especially in manual assembly lines, the tasks may have varying execution times defined as a probability distribution. In this paper, the mixed-model U-line balancing and sequencing problem with stochastic task times is considered. For this purpose, a genetic algorithm is developed to solve the problem. To assess the effectiveness of the proposed algorithm, a computational study is conducted for both deterministic and stochastic versions of the problem.en_US
dc.description.sponsorshipGazi UniversityGazi University [06/2009-10]en_US
dc.description.sponsorshipThis research was supported by the Gazi University Scientific Research Projects Grant Number 06/2009-10. We thank the anonymous referees for their valuable comments that significantly improved the presentation of this paper.en_US
dc.identifier.citationclosedAccessen_US
dc.identifier.doi10.1080/00207541003690090
dc.identifier.endpage1626en_US
dc.identifier.issn0020-7543
dc.identifier.issue6en_US
dc.identifier.scopus2-s2.0-78650589919
dc.identifier.scopusqualityQ1
dc.identifier.startpage1605en_US
dc.identifier.urihttps://doi.org/10.1080/00207541003690090
dc.identifier.urihttps://hdl.handle.net/20.500.12587/5095
dc.identifier.volume49en_US
dc.identifier.wosWOS:000285413400005
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofInternational Journal Of Production Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectassembly line balancingen_US
dc.subjectU-linesen_US
dc.subjectmixed-model productionen_US
dc.subjectstochasticen_US
dc.subjectgenetic algorithmsen_US
dc.titleA genetic algorithm for the stochastic mixed-model U-line balancing and sequencing problemen_US
dc.typeArticle

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