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An Analytic Framework for Evaluating Rolling Schedules

Author

Listed:
  • Kenneth R. Baker

    (Duke University)

  • David W. Peterson

    (Duke University)

Abstract

A rolling schedule is formed by solving a multi-period problem and implementing only the first period's decisions; one period later the multi-period model is updated and the process repeated. In this paper, we provide a general framework for analyzing rolling schedules, and we examine analytically a fundamental quadratic-cost model for the effects of such factors as the length of the planning interval, the uncertainty in forecasts, and the periodicity of demand. For the quadratic model our main result is that cost performance improves monotonically as the planning horizon is lengthened. We also find that the use of terminal conditions in the multi-period model can dramatically improve rolling schedule performance.

Suggested Citation

  • Kenneth R. Baker & David W. Peterson, 1979. "An Analytic Framework for Evaluating Rolling Schedules," Management Science, INFORMS, vol. 25(4), pages 341-351, April.
    • Handle: RePEc:inm:ormnsc:v:25:y:1979:i:4:p:341-351
    DOI: 10.1287/mnsc.25.4.341
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    Citations

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    Cited by:

    1. Kimms, A, 1998. "Stability Measures for Rolling Schedules with Applications to Capacity Expansion Planning, Master Production Scheduling, and Lot Sizing," Omega, Elsevier, vol. 26(3), pages 355-366, June.
    2. Haeussler, S. & Stampfer, C. & Missbauer, H., 2020. "Comparison of two optimization based order release models with fixed and variable lead times," International Journal of Production Economics, Elsevier, vol. 227(C).
    3. Bradley Franklin & Keith C. Knapp & Kurt A. Schwabe, 2017. "A Dynamic Regional Model of Irrigated Perennial Crop Production," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 1-30, January.
    4. Cattani, Kyle D., 2016. "Fenced in? Stochastic and deterministic planning models in a time-fenced, rolling-horizon scheduling systemAuthor-Name: DeYong, Gregory D," European Journal of Operational Research, Elsevier, vol. 251(1), pages 85-95.
    5. Kriett, Phillip Oliver & Salani, Matteo, 2012. "Optimal control of a residential microgrid," Energy, Elsevier, vol. 42(1), pages 321-330.
    6. Kimms, Alf, 1996. "Stability measures for rolling schedules with applications to capacity expansion planning, master production scheduling, and lot sizing," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 418, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    7. Salewski, Frank & Nissen, Rüdiger, 1993. "Revidierende hierarchische Planung: Ein Konzept am Beispiel der Personaleinsatzplanung in Wirtschaftsprüfungsgesellschaften," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 335, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    8. Schütz, Peter & Tomasgard, Asgeir, 2011. "The impact of flexibility on operational supply chain planning," International Journal of Production Economics, Elsevier, vol. 134(2), pages 300-311, December.
    9. Hartmut Stadtler, 2000. "Improved Rolling Schedules for the Dynamic Single-Level Lot-Sizing Problem," Management Science, INFORMS, vol. 46(2), pages 318-326, February.
    10. Wijngaard, J., 2004. "The effect of foreknowledge of demand in case of a restricted capacity: The single-stage, single-product case," European Journal of Operational Research, Elsevier, vol. 159(1), pages 95-109, November.
    11. Suwa, Haruhiko, 2007. "A new when-to-schedule policy in online scheduling based on cumulative task delays," International Journal of Production Economics, Elsevier, vol. 110(1-2), pages 175-186, October.
    12. Ryan, Sarah M., 1998. "Forecast frequency in rolling horizon hedging heuristics for capacity expansion," European Journal of Operational Research, Elsevier, vol. 109(3), pages 550-558, September.
    13. Salewski, Frank, 1994. "An integrative approach to audit-staff scheduling," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 358, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    14. repec:dgr:rugsom:02a15 is not listed on IDEAS
    15. Wijngaard, J., 2002. "The effect of foreknowledge of demand in case of a restricted capacity: the single-stage, singleproduct case with lost sales," Research Report 02A15, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    16. Suresh Chand & Vernon Ning Hsu & Suresh Sethi, 2002. "Forecast, Solution, and Rolling Horizons in Operations Management Problems: A Classified Bibliography," Manufacturing & Service Operations Management, INFORMS, vol. 4(1), pages 25-43, September.
    17. Garay-Sianca, Aniela & Nurre Pinkley, Sarah G., 2021. "Interdependent integrated network design and scheduling problems with movement of machines," European Journal of Operational Research, Elsevier, vol. 289(1), pages 297-327.
    18. Zhaotong Lian & Liming Liu & Stuart X. Zhu, 2010. "Rolling‐horizon replenishment: Policies and performance analysis," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(6), pages 489-502, September.

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