Article ID: | iaor20042051 |
Country: | United Kingdom |
Volume: | 41 |
Issue: | 17 |
Start Page Number: | 4153 |
End Page Number: | 4169 |
Publication Date: | Jan 2003 |
Journal: | International Journal of Production Research |
Authors: | Taner Mehmet R., Hodgson Thomas J., King Russell, E., Thoney Kristin A. |
Keywords: | markov processes |
This paper addresses job shop scheduling with sequence dependent family set-ups. Based on a simple, single-machine dynamic scheduling problem, state dependent scheduling rules for the single machine problem are developed and tested using Markov Decision Processes. Then, a generalized scheduling policy for the job shop problem is established based on a characterization of the optimal policy. The policy is combined with a ‘forecasting’ mechanism to utilize global shop floor information for local dispatching decisions. Computational results show that performance is significantly better than that of existing alternative policies.