A genetic algorithm for the stochastic mixed-model U-line balancing and sequencing problem
dc.contributor.author | Ozcan, Ugur | |
dc.contributor.author | Kellegoz, Talip | |
dc.contributor.author | Toklu, Bilal | |
dc.date.accessioned | 2020-03-26T18:08:13Z | |
dc.date.available | 2020-03-26T18:08:13Z | |
dc.date.issued | 2011 | |
dc.department | Selçuk Üniversitesi | en_US |
dc.description.abstract | Mixed-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.sponsorship | Gazi UniversityGazi University [06/2009-10] | en_US |
dc.description.sponsorship | This 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.doi | 10.1080/00207541003690090 | en_US |
dc.identifier.endpage | 1626 | en_US |
dc.identifier.issn | 0020-7543 | en_US |
dc.identifier.issue | 6 | en_US |
dc.identifier.scopusquality | Q1 | en_US |
dc.identifier.startpage | 1605 | en_US |
dc.identifier.uri | https://dx.doi.org/10.1080/00207541003690090 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12395/26052 | |
dc.identifier.volume | 49 | en_US |
dc.identifier.wos | WOS:000285413400005 | en_US |
dc.identifier.wosquality | Q2 | en_US |
dc.indekslendigikaynak | Web of Science | en_US |
dc.indekslendigikaynak | Scopus | en_US |
dc.language.iso | en | en_US |
dc.publisher | TAYLOR & FRANCIS LTD | en_US |
dc.relation.ispartof | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.selcuk | 20240510_oaig | en_US |
dc.subject | assembly line balancing | en_US |
dc.subject | U-lines | en_US |
dc.subject | mixed-model production | en_US |
dc.subject | stochastic | en_US |
dc.subject | genetic algorithms | en_US |
dc.title | A genetic algorithm for the stochastic mixed-model U-line balancing and sequencing problem | en_US |
dc.type | Article | en_US |