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Heavy Traffic Analysis of Dynamic Cyclic Policies: A Unified Treatment of the Single Machine Scheduling Problem

Author

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  • David M. Markowitz

    (Program Analysis and Evaluation, Office of the Secretary of Defense, Washington, District of Columbia 20301-1800)

  • Lawrence M. Wein

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142)

Abstract

This paper examines how setups, due dates, and the mix of standardized and customized products affect the scheduling of a single machine operating in a dynamic and stochastic environment. We restrict ourselves to the class of dynamic cyclic policies, where the machine busy/idle policy and lot-sizing decisions are controlled in a dynamic fashion, but different products must be produced in a fixed sequence. As in earlier work, we conjecture that an averaging principle holds for this queueing system in the heavy traffic limit, and optimize over the class of dynamic cyclic policies. The results allow for a detailed discussion of the interactions between the due-date, setup, and product mix facets of the problem.

Suggested Citation

  • David M. Markowitz & Lawrence M. Wein, 2001. "Heavy Traffic Analysis of Dynamic Cyclic Policies: A Unified Treatment of the Single Machine Scheduling Problem," Operations Research, INFORMS, vol. 49(2), pages 246-270, April.
  • Handle: RePEc:inm:oropre:v:49:y:2001:i:2:p:246-270
    DOI: 10.1287/opre.49.2.246.13530
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    References listed on IDEAS

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    Cited by:

    1. Germs, Remco & Van Foreest, Nicky D., 2011. "Admission policies for the customized stochastic lot scheduling problem with strict due-dates," European Journal of Operational Research, Elsevier, vol. 213(2), pages 375-383, September.
    2. Winands, E.M.M. & Adan, I.J.B.F. & van Houtum, G.J., 2011. "The stochastic economic lot scheduling problem: A survey," European Journal of Operational Research, Elsevier, vol. 210(1), pages 1-9, April.
    3. René Caldentey & Lawrence M. Wein, 2006. "Revenue Management of a Make-to-Stock Queue," Operations Research, INFORMS, vol. 54(5), pages 859-875, October.
    4. Lopez de Haro, Santiago & Gershwin, Stanley B. & Rosenfield, Donald B., 2009. "Schedule evaluation in unstable manufacturing environments," International Journal of Production Economics, Elsevier, vol. 121(1), pages 183-194, September.
    5. Otis B. Jennings, 2008. "Heavy-Traffic Limits of Queueing Networks with Polling Stations: Brownian Motion in a Wedge," Mathematics of Operations Research, INFORMS, vol. 33(1), pages 12-35, February.
    6. Han Wu & Gerald Evans & Ki-Hwan Bae, 2016. "Production control in a complex production system using approximate dynamic programming," International Journal of Production Research, Taylor & Francis Journals, vol. 54(8), pages 2419-2432, April.
    7. Wei-Min Lan & Tava Lennon Olsen, 2006. "Multiproduct Systems with Both Setup Times and Costs: Fluid Bounds and Schedules," Operations Research, INFORMS, vol. 54(3), pages 505-522, June.
    8. Jan A. Van Mieghem, 2003. "Due-Date Scheduling: Asymptotic Optimality of Generalized Longest Queue and Generalized Largest Delay Rules," Operations Research, INFORMS, vol. 51(1), pages 113-122, February.
    9. Donald D. Eisenstein, 2005. "Recovering Cyclic Schedules Using Dynamic Produce-Up-To Policies," Operations Research, INFORMS, vol. 53(4), pages 675-688, August.

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