A study of factors affecting due date predictibility for on-time delivery in a dynamic job shop

Authors:
Şerafettin Alpay;Nihat Yüzügüllü
Affiliations:
Eskişehir Osmangazi University, Eskişehir, Turkiye;Eskişehir Osmangazi University, Eskişehir, Turkiye
Venue:
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Year:
2006

Citing 3
Cited 0

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Abstract

In this research, the factors have significant effect on due date predictability for on time delivery in a dynamic job shop were studied. For this aim a new due date assignment model was proposed and an experimental study in a simulated dynamic job shop was performed. The results indicate that the proposed due date assignment model is adequate to meet the assigned due dates for on time delivery and the number of jobs in the queues of the machines on a job's route is the most important factor affects the due date predictability.