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Repair strategies in an uncertain environment: Markov decision process approach

Author

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  • Y-H Kim

    (University of Southampton)

  • L C Thomas

    (University of Southampton)

Abstract

This paper deals with repair strategies that maximize the time until a catastrophic event, that is, when there is a vital need for equipment, and the equipment fails to function. We examine the case where the need for the equipment varies over time according to a Markov chain. This means that the environment can be in different states, each with their own probability of the initiating event occurring. We model the form of the optimal policy for repair under this uncertain environment by Markov decision processes.

Suggested Citation

  • Y-H Kim & L C Thomas, 2006. "Repair strategies in an uncertain environment: Markov decision process approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(8), pages 957-964, August.
    • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:8:d:10.1057_palgrave.jors.2602048
    DOI: 10.1057/palgrave.jors.2602048
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    References listed on IDEAS

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    1. John J. McCall, 1965. "Maintenance Policies for Stochastically Failing Equipment: A Survey," Management Science, INFORMS, vol. 11(5), pages 493-524, March.
    2. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    3. Çinlar, Erhan & Shaked, Moshe & Shanthikumar, J. George, 1989. "On lifetimes influenced by a common environment," Stochastic Processes and their Applications, Elsevier, vol. 33(2), pages 347-359, December.
    4. George E. Monahan, 1982. "State of the Art---A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms," Management Science, INFORMS, vol. 28(1), pages 1-16, January.
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    Cited by:

    1. Yeek-Hyun Kim & Lyn Thomas, 2013. "Training and repair policies for stand-by systems," Annals of Operations Research, Springer, vol. 208(1), pages 469-487, September.

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