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A simple suboptimal algorithm for system maintenanceunder partial observability

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  • I. David
  • L. Friedman
  • Z. Sinuany‐Stern

Abstract

We suggest a heuristic solution procedure for Partially Observable Markov DecisionProcesses with finite action space and finite state space with infinite horizon. The algorithmis a fast, very simple general heuristic; it is applicable for multiple states (not necessarilyordered) multiple actions and various distribution functions. The quality of the algorithm ischecked in this paper against existing analytical and empirical results for two specific modelsof machine replacement. One model refers to the case of two‐action and two‐system stateswith uniform observations (Grosfeld‐Nir [4]), and the other model refers to a case of manyordered states with binomial observations (Sinuany‐Stern et al. [11]). The paper also presentsthe model realization for various probability distribution functions applied to maintenanceand quality control. Copyright Kluwer Academic Publishers 1999

Suggested Citation

  • I. David & L. Friedman & Z. Sinuany‐Stern, 1999. "A simple suboptimal algorithm for system maintenanceunder partial observability," Annals of Operations Research, Springer, vol. 91(0), pages 25-40, January.
    • Handle: RePEc:spr:annopr:v:91:y:1999:i:0:p:25-40:10.1023/a:1018949723461
    DOI: 10.1023/A:1018949723461
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    Cited by:

    1. Sinuany-Stern, Zilla, 2023. "Foundations of operations research: From linear programming to data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1069-1080.
    2. Aiden Fisher & David Green & Andrew Metcalfe, 2012. "Modelling of hydrological persistence for hidden state Markov decision processes," Annals of Operations Research, Springer, vol. 199(1), pages 215-224, October.

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