Online due date assignment in dynamic and stochastic scheduling environments with family setups under tardiness and quoted lead time considerations
| dc.contributor | Ph.D. Program in Industrial Engineering. | |
| dc.contributor.advisor | Ünal, Ali Tamer. | |
| dc.contributor.author | Düzgit, Zehra. | |
| dc.date.accessioned | 2023-03-16T10:35:22Z | |
| dc.date.available | 2023-03-16T10:35:22Z | |
| dc.date.issued | 2015. | |
| dc.description.abstract | In this study, due date assignment problem is addressed in a single machine dynamic and stochastic environment with family setups. A due date is to be assigned for each new job immediately at the time of its arrival. While assigning a due date for a new arrival, non-complete jobs that have arrived before that job and whose due dates are already assigned, are also considered and rescheduled. While assigning a short due date for a new arrival as close as possible, compliance to assigned due dates of noncomplete jobs is necessary. These two objectives con ict with each other. In order to solve this problem, a two-phase solution methodology is proposed. In the rst phase, a capacity allocation takes place for families before observing any actual jobs arrivals, based on expected work load and arrival estimation, in a periodic and static manner. In this phase, families can be assigned to batches and a batching structure is formed. In the second phase, a due date is assigned for the new arrival immediately in an online fashion, based on the outputs of the rst phase. A mixed integer programming model and a heuristic algorithm are developed for each phase. Simultaneously, a discrete event simulation is carried out to imitate a real production system. The performance of the designed batching policy is measured through the developed simulation model and results are reported under di erent system parameters. | |
| dc.format.extent | 30 cm. | |
| dc.format.pages | xix, 145 leaves ; | |
| dc.identifier.other | IE 2015 D88 PhD | |
| dc.identifier.uri | https://digitalarchive.library.bogazici.edu.tr/handle/123456789/13563 | |
| dc.publisher | Thesis (Ph.D.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2015. | |
| dc.subject.lcsh | Intelligent control systems. | |
| dc.title | Online due date assignment in dynamic and stochastic scheduling environments with family setups under tardiness and quoted lead time considerations |
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