Abstract
The development of production plans for the CIM hierarchy directs the firm’s manufacturing activities over an extended time horizon. All of the subordinate CIM functions (e.g. production scheduling, material and capacity requirements planning, purchasing, and others) are impacted by this plan. The first step in the development of a production plan is the specification of an appropriate planning horizon--a complex task that is plagued with numerous uncertainties. To address this task, this paper views the production planning problem as a two-point boundary value problem where boundary conditions must be specified at both the beginning and at the end of the planning horizon. A difficulty arises in the specification of the ending boundary conditions since they are generally unknown. Furthermore, an incorrect specification can have a significant, perhaps detrimental, effect upon the quality of the developed plan. An additional requirement for the planning horizon is that it be of suitable duration to permit an effective integration of production planning with the other CIM functions.
The reported research addresses the uncertainties in specifying the boundary conditions. An integrated solution approach that employs both Monte Carlo simulation and mathematical programming is used to consider the inherent uncertainties associated with the production planning problem. For the considered computational examples, it is shown that the specification of boundary conditions do effect the quality of the derived production plan. Furthermore, the results also suggest that planning epochs exist. The observation of planning epochs implies that a variable length planning horizon, rather than a constant length horizon, should be employed within the context of a rolling horizon implementation of production planning. Using this approach, the planning would be performed to the end of the current epoch where boundary conditions can be specified with greater accuracy. Finally, the issue of establishing the length of an epoch is discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Baker, G. R., and Peterson, D. W., “An Analytic Framework for Evaluating Rolling Schedules,” Management Science, Vol. 25, 1979, pp. 341–351.
Britran, G. R., Haas, E. A., and Hax, A. C., “Hierarchical Production Planning: Single Stage System,” Operations Research, Vol. 29, 1981, pp. 717–743.
Bitran, G. R., Haas, E. A., and Hax, A. C., “Hierarchical Production Planning: A Two-Stage Systems,” Operations Research, Vol. 30, 1982, pp. 232–251.
Britran, G. R., and Hax, A. C., “On the Design of Hierarchical Production Planning Systems,” Decision Sciences, Vol.8, 1977, pp. 38–55.
Bookbinder, J. H., and H’ng, B. T., “Rolling Horizon Production Planning for Probabilistic Time-Varying Demands,” International Journal of Production Research, Vol. 24, 1986, pp. 1439–1458.
Carlson, R. C., Beckman S. L., and Kropp, D. H., “The Effectiveness of Extending the Horizon in Rolling Production Scheduling,” Decision Sciences, Vol. 13, 1982, pp. 129–146.
Chung, C., Chen, I., and Cheng G. L. Y.,“Planning Horizons for Multi-Item Hierarchical Production Scheduling Problems: A Heuristic Search Procedure,” European Journal of Operational Research, Vol. 37, 1988, pp. 368–377.
Davis, W. J., Thompson, S. D., and White, L. R., “The Importance of Decompositions in CIM Control Architectures,” in Proceedings of CIMCON ’90, ed. Albert Jones, National Institute of Standards and Technology, NIST Special Publication 785, Gaithersburg, MD, May 1990, pp. 466–486.
Davis, W. J., Thompson, S. D., and White, L. R., “Decision Making and Control Schema for Production Planning in CIM Systems”, Joint US/German Conference on New Directions for Operations Research in Manufacturing, National Institute of Standards and Technology, Gaithersburg, MD, 1991 (in press).
Eppen, G.D., Gould, F.J., and Pashigian, B.P., “Extensions of the Planning Horizon Theorem in the Dynamic Lot Size Model,” Management Science, Vol. 15, 1968, pp. 268–277.
Kunreuther, H. C., and Morton, T. E., “Planning Horizons for Production Smoothing with Deterministic Demands - I. All Demand Met from Regular Production,” Management Science, Vol. 20, 1973, pp. 110–125.
Kunreuther, H. C., and Morton, T. E., “General Planning Horizons for Production Smoothing with Deterministic Demands - II. Extensions to Overtime, Undertime, and Backlogging,” Management Science Vol. 20, 1974, pp. 1037–1046.
Marsten, R. E., “The Design of the XMP Linear Programming Library,” ACM Transactions on Mathematical Software, Vol. 7, 1981, pp. 481–497.
McClain, J. O., and Thomas, J., “Horizon Effects in Aggregate Production Planning with Seasonal Demand,” Management Science, Vol. 23, 1977, pp. 728–736.
Miller, L. W., “Using Linear Programming to Derive Planning Horizons for a Production Smoothing Problem,” Management Science, Vol. 25, 1979, pp. 1232–1244.
Nagasawa, H., Nishiyama, N., and Hitomi, K., “Decision Analysis for Determining the Optimum Planning Horizon in Aggregate Production Planning,” International Journal of Production Research, Vol. 20, 1982, pp. 243–254.
Nagasawa, H., Nishiyama, N., and Hitomi, K., “Decision Analysis for Determining the Optimum Planning Horizon in Aggregate Production Planning. Part 2: Difference Between Planning Horizons in Weekly and in Monthly Schedulings,” International Journal of Production Research, Vol. 23, 1985, pp. 423–436.
Pekelman, D., “Production Smoothing with Fluctuating Price,” Management Science, Vol. 21, 1975, pp. 576–590.
Sastri, T., and Feiring, B. R., “Sequential Optimization and Revision of Production Plans Over Time,” Computers in Industrial Engineering, Vol. 17, 1989, pp. 372–377.
Sridharan, V., Berry, W. L., and Udayabhanu, V., “Freezing the Master Production Schedule Under Rolling Planning Horizons,” Management Science, Vol. 33, 1987, pp. 1137–1149.
Thompson, S. D., and Davis, W. J., “An Integrated Approach for Modeling Uncertainty in Aggregate Production Planning,” IEEE Transactions on Systems, Man, and Cybernetics, Vol. 20, 1990, pp. 1000–1012.
Wagner, H.M., and Whitin, T.M., “Dynamic Version of the Economic Lot Size Model,” Management Science, Vol. 5, 1958, pp. 89–96.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1993 Springer-Verlag Berlin· Heidelberg
About this paper
Cite this paper
Thompson, S.D., Jewell, J.A., Davis, W.J. (1993). Issues in Specifying Planning Horizons for Production Planning within CIM Environments. In: Fandel, G., Gulledge, T., Jones, A. (eds) Operations Research in Production Planning and Control. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-78063-9_17
Download citation
DOI: https://doi.org/10.1007/978-3-642-78063-9_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-78065-3
Online ISBN: 978-3-642-78063-9
eBook Packages: Springer Book Archive