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Forecast Horizons in the Discounted Dynamic Lot Size Model

Author

Listed:
  • Suresh Chand

    (Krannert Graduate School of Management, Purdue University, West Lafayette, Indiana 47907)

  • Suresh P. Sethi

    (Faculty of Management, University of Toronto, 246 Bloor St. West, Toronto, Ontario, Canada M5S 1V4)

  • Gerhard Sorger

    (Department of Economics, University of Vienna, Liechtensteinstrasse 13, A-1090 Vienna, Austria)

Abstract

We derive a sharp upper bound on the minimal forecast horizon in the discounted dynamic lot size model with constant initial demand. This bound is given by m(m + 1), where m is the EOQ's worth, i.e., the number of periods for which the total demand equals Economic Order Quantity. Our results do not require the solution of the infinite horizon problem to be unique. Nor do they require the infinite horizon problem to be well defined. We also prove some sensitivity results with respect to the discount factor and the setup cost.

Suggested Citation

  • Suresh Chand & Suresh P. Sethi & Gerhard Sorger, 1992. "Forecast Horizons in the Discounted Dynamic Lot Size Model," Management Science, INFORMS, vol. 38(7), pages 1034-1048, July.
    • Handle: RePEc:inm:ormnsc:v:38:y:1992:i:7:p:1034-1048
    DOI: 10.1287/mnsc.38.7.1034
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    Citations

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    Cited by:

    1. Hartmut Stadtler & Malte Meistering, 2019. "Model formulations for the capacitated lot-sizing problem with service-level constraints," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(4), pages 1025-1056, December.
    2. Marshall Fisher & Kamalini Ramdas & Yu-Sheng Zheng, 2001. "Ending Inventory Valuation in Multiperiod Production Scheduling," Management Science, INFORMS, vol. 47(5), pages 679-692, May.
    3. Jans, R.F. & Degraeve, Z., 2005. "Modeling Industrial Lot Sizing Problems: A Review," ERIM Report Series Research in Management ERS-2005-049-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Ram Rachamadugu & Ranga Ramasesh, 1994. "Suboptimality of equal lot sizes for finite‐horizon problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 41(7), pages 1019-1027, December.
    5. Hartmut Stadtler, 2000. "Improved Rolling Schedules for the Dynamic Single-Level Lot-Sizing Problem," Management Science, INFORMS, vol. 46(2), pages 318-326, February.
    6. Bylka, S.Stanislaw & Rempala, Ryszarda, 2004. "Heuristics for impulse replenishment with continuous periodic demand," International Journal of Production Economics, Elsevier, vol. 88(2), pages 183-190, March.
    7. Balakrishnan, Jaydeep & Hung Cheng, Chun, 2009. "The dynamic plant layout problem: Incorporating rolling horizons and forecast uncertainty," Omega, Elsevier, vol. 37(1), pages 165-177, February.
    8. Fuying Jing & Zirui Lan, 2017. "Forecast horizon of multi-item dynamic lot size model with perishable inventory," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-15, November.
    9. Awi Federgruen & Michal Tzur, 1993. "The dynamic lot‐sizing model with backlogging: A simple o(n log n) algorithm and minimal forecast horizon procedure," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(4), pages 459-478, June.
    10. Archis Ghate & Robert L. Smith, 2009. "Optimal Backlogging Over an Infinite Horizon Under Time-Varying Convex Production and Inventory Costs," Manufacturing & Service Operations Management, INFORMS, vol. 11(2), pages 362-368, June.
    11. Awi Federgruen & Michal Tzur, 1996. "Detection of minimal forecast horizons in dynamic programs with multiple indicators of the future," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(2), pages 169-189, March.
    12. 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.

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