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A Fluid Model for Systems with Random Disruptions

Author

Listed:
  • Hong Chen

    (University of British Columbia, Vancouver, Canada and New Jersey Institute of Technology, Newark, New Jersey)

  • David D. Yao

    (Columbia University, New York, New York)

Abstract

Motivated by modeling manufacturing systems in which job arrivals and processing times are essentially deterministic, but the environment is typically random, we develop a fluid model with random disruptions. The quality and relevance of such a model are supported by the following facts which we establish in this study. The fluid model is more susceptible to analysis: Its (dynamical) sample paths are continuous and piecewise linear, and its stationary behavior can be studied using standard approaches in random walk; the model is a limit of corresponding queueing systems with random disruptions that are usually difficult to analyze; there exist pathwise bounds between the fluid model and D / D /1 queues with random disruptions, and the bounds are simple and tight.

Suggested Citation

  • Hong Chen & David D. Yao, 1992. "A Fluid Model for Systems with Random Disruptions," Operations Research, INFORMS, vol. 40(3-supplem), pages 239-247, June.
    • Handle: RePEc:inm:oropre:v:40:y:1992:i:3-supplement-2:p:s239-s247
    DOI: 10.1287/opre.40.3.S239
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    Citations

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    Cited by:

    1. Boxma, O. J. & Perry, D., 2001. "A queueing model with dependence between service and interarrival times," European Journal of Operational Research, Elsevier, vol. 128(3), pages 611-624, February.
    2. Arnoud den Boer & Ohad Perry & Bert Zwart, 2018. "Dynamic pricing policies for an inventory model with random windows of opportunities," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(8), pages 660-675, December.
    3. Guodong Pang & Ward Whitt, 2009. "Service Interruptions in Large-Scale Service Systems," Management Science, INFORMS, vol. 55(9), pages 1499-1512, September.
    4. Mohebbi, E., 2008. "A note on a production control model for a facility with limited storage capacity in a random environment," European Journal of Operational Research, Elsevier, vol. 190(2), pages 562-570, October.
    5. Andrew M. Ross, 2009. "Distribution sensitivity in a highway flow model," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(6), pages 769-786, November.
    6. Mohebbi, Esmail, 2006. "A production-inventory model with randomly changing environmental conditions," European Journal of Operational Research, Elsevier, vol. 174(1), pages 539-552, October.
    7. Van der Duyn Schouten, F. A. & Vanneste, S. G., 1995. "Maintenance optimization of a production system with buffer capacity," European Journal of Operational Research, Elsevier, vol. 82(2), pages 323-338, April.

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