Arşiv ve Dokümantasyon Merkezi
Dijital Arşivi

Analysis of the impact of decision time on the system performance in distributed systems

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dc.contributor Ph.D. Program in Industrial Engineering.
dc.contributor.advisor Ünal, Ali Tamer.
dc.contributor.author Özgün, Kamer.
dc.date.accessioned 2023-03-16T10:35:19Z
dc.date.available 2023-03-16T10:35:19Z
dc.date.issued 2012.
dc.identifier.other IE 2012 O85 PhD
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/13550
dc.description.abstract In this study, we investigate the e ect of the time it takes to generate a schedule on the performance of a stochastic dynamic scheduling system. To isolate the impact of the decision time on the system performance, we devise a single machine stochastic scheduling environment where the performance of the system is measured by average earliness - tardiness cost. Our study is composed of two phases. In the rst phase, we construct a centralized scheduling system. We explicitly model the decision time. We test the trade o between spending more time for the scheduling process by employing more sophisticated scheduling algorithms and using simple fast heuristic algorithm. In the second phase, we construct a distributed scheduling system. We test the trade o between spending more time by including detailed global information to achieve global optimality under a centralized control structure and using timely accessible local information under distributed control. We simulated the system under various scheduling environments controlled by due date tightness, urgent job ratios, operation time variability and utilization using di erent centralized control polices and distributed control policies. Our experiments show that under certain shop conditions and control policies, the shop may operate more e ciently if a simple fast heuristic is used instead of a slow optimum algorithm to solve the scheduling problems. We have been able to also show that, again under some speci c operating conditions, the dynamic production system will run more e ciently when we use fast distributed schedulers instead of a relatively slow centralized scheduler.
dc.format.extent 30 cm.
dc.publisher Thesis (Ph.D.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2012.
dc.relation Includes appendices.
dc.relation Includes appendices.
dc.subject.lcsh Electronic data processing -- Distributed processing -- Computer simulation.
dc.subject.lcsh Electronic data processing -- Distributed processing -- Mathematical models.
dc.subject.lcsh Artificial intelligence -- Data processing.
dc.title Analysis of the impact of decision time on the system performance in distributed systems
dc.format.pages xviii, 124 leaves ;


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