Abstract
Aggregate models of detailed scheduling problems are needed to support aggregate decision making such as customer order acceptance. In this paper, we explore the performance of various aggregate models in a decentralized control setting in batch chemical manufacturing (no-wait job shops). Using simulation experiments based on data extracted from an industry application, we conclude that a linear regression based model outperforms a workload based model with regard to capacity utilization and the need for replanning at the decentralized level, specifically in situations with increased capacity utilization and/or a high variety in the job mix.
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References
Akkan, C. (1997) Finite-capacity scheduling-based planning for revenue-based capacity management. European Journal of Operational Research, 100, 170–179.
Bertrand, J.W.M. (1983) The effect of workload dependent due-dates on job shop performance. Management Science, 29, 799–816.
Carlier, J. (1987) Scheduling jobs with release dates and tails on identical machines to minimize the makespan. European Journal of Operational Research, 29, 298–306.
Enns, S.T. (1993) Job shop flowtime prediction and tardiness control using queueing analysis. International Journal of Production Research, 31, 2045–2057.
Enns, S.T. (1995) A dynamic forecasting model for job shop flow-time prediction and tardiness control. International Journal of Production Research, 33, 1295–1312.
Guerrero, H.H. and Kern, G.M. (1988) How to more effectively accept and refuse orders. Production and Inventory Management, 29 (4), 59–62.
Kern, G.M. and Guerrero, H.H. (1990) A conceptual model for demand management in the assemble-to-order environment. Journal of Operations Management, 9, 65–84.
Raaymakers, W.H.M., Bertrand, J.W.M. and Fransoo, J.C. (2000) Aggregation principles in hierarchical production planning in a batch chemical plant. Journal of Intelligent Manufacturing, 11(2), 217–228.
Raaymakers, W.H.M. and Fransoo, J.C. (1999) Identification of aggregate resource and job set characteristics for predicting job set makespan in batch process industries. International Journal of Production Economics, (in press).
Raaymakers, W.H.M. and Hoogeveen, J.A. (1999) Scheduling multi-purpose batch process industries with no-wait restrictions by simulated annealing. European Journal of Operational Research, (in press).
Sgall, J. (1998) On-line scheduling, in: Online Algorithms: The State of the Art, Fiat, A. and Woeginger, G.J. (eds.), Springer, Berlin, pp. 198–231.
Ten Kate, H.A. (1994) Towards a better understanding of order acceptance. International Journal of Production Economics, 37, 139–152.
van Bael, P. (1999) A study of rescheduling strategies and abstraction levels for a chemical process scheduling problem. Production Planning and Control, 10, 359–364.
Wang, J., Yang, J.Q. and Lee, H. (1994) Multicriteria order acceptance decision support in over-demanded job shops: a neural network approach. Mathematical and Computer Modeling, 19(5), 1–19.
Wester, F.A.W., Wijngaard, J. and Zijm, W.H.M. (1992) Order acceptance strategies in a production-to-order environment with setup times and due-dates. International Journal of Production Research, 30, 1313–1326.
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Raaymakers, W.H., Bertrand, J.W.M. & Fransoo, J.C. Using aggregate estimation models for order acceptance in a decentralized production control structure for batch chemical manufacturing. IIE Transactions 32, 989–998 (2000). https://doi.org/10.1023/A:1007672800764
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DOI: https://doi.org/10.1023/A:1007672800764