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The Dynamic Lot-Size Model with Stochastic Lead Times

Author

Listed:
  • Christopher Nevison

    (Colgate University)

  • Michael Burstein

    (University of Massachusetts)

Abstract

Optimal solutions for the dynamic lot-sizing problem with deterministic demands but stochastic lead times are "lumpy." If lead time distributions are arbitrary except that they are independent of order size and do not allow orders to cross in time, then each order in an optimal solution will exactly satisfy a consecutive sequence of demands, a natural extension of the classic results by Wagner and Whitin. If, on the other hand, orders can cross in time, then optimal solutions are still "lumpy" in the sense that each order will satisfy a set, not necessarily consecutive, of the demands. An example shows how this characterization can be used to find a solution to a problem where interdependence of lead times is critical. This characterization of optimal solutions facilitates dynamic programming approaches to this problem.

Suggested Citation

  • Christopher Nevison & Michael Burstein, 1984. "The Dynamic Lot-Size Model with Stochastic Lead Times," Management Science, INFORMS, vol. 30(1), pages 100-109, January.
    • Handle: RePEc:inm:ormnsc:v:30:y:1984:i:1:p:100-109
    DOI: 10.1287/mnsc.30.1.100
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    Citations

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    Cited by:

    1. Osman Alp & Nesim K. Erkip & Refik Güllü, 2003. "Optimal Lot-Sizing/Vehicle-Dispatching Policies Under Stochastic Lead Times and Stepwise Fixed Costs," Operations Research, INFORMS, vol. 51(1), pages 160-166, February.
    2. Thevenin, Simon & Ben-Ammar, Oussama & Brahimi, Nadjib, 2022. "Robust optimization approaches for purchase planning with supplier selection under lead time uncertainty," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1199-1215.
    3. Achin Srivastav & Sunil Agrawal, 2020. "On a single item single stage mixture inventory models with independent stochastic lead times," Operational Research, Springer, vol. 20(4), pages 2189-2227, December.
    4. Roberto Rossi & S. Armagan Tarim & Ramesh Bollapragada, 2012. "Constraint-Based Local Search for Inventory Control Under Stochastic Demand and Lead Time," INFORMS Journal on Computing, INFORMS, vol. 24(1), pages 66-80, February.
    5. Riezebos, Jan & Zhu, Stuart X., 2020. "Inventory control with seasonality of lead times," Omega, Elsevier, vol. 92(C).
    6. Riezebos, Jan, 2006. "Inventory order crossovers," International Journal of Production Economics, Elsevier, vol. 104(2), pages 666-675, December.
    7. Rossi, Roberto & Tarim, S. Armagan & Hnich, Brahim & Prestwich, Steven, 2010. "Computing the non-stationary replenishment cycle inventory policy under stochastic supplier lead-times," International Journal of Production Economics, Elsevier, vol. 127(1), pages 180-189, September.
    8. 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.
    9. Achin Srivastav & Sunil Agrawal, 2020. "Multi-objective optimization of mixture inventory system experiencing order crossover," Annals of Operations Research, Springer, vol. 290(1), pages 943-960, July.

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