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Optimality of randomized strategies in a Markovian replacement model

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  • Peter Bruns

Abstract

We study a replacement system with discrete-time Markovian deterioration and finite state space {0, …,N}. State 0 stands for a new system, and the larger the state the worse the condition of the system with N as the failure state. We impose the condition that the long-term fraction of replacements in state N should not be larger than some fixed number. We prove that a generalized control-limit policy maximizes the expected time between two successive replacements and we explain explicitly how to derive this (randomized) optimal policy. Some numerical examples are given. Copyright Springer-Verlag Berlin Heidelberg 2003

Suggested Citation

  • Peter Bruns, 2003. "Optimality of randomized strategies in a Markovian replacement model," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 56(3), pages 481-499, January.
    • Handle: RePEc:spr:mathme:v:56:y:2003:i:3:p:481-499
    DOI: 10.1007/s001860200236
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    Cited by:

    1. Oguzhan Alagoz & Lisa M. Maillart & Andrew J. Schaefer & Mark S. Roberts, 2007. "Determining the Acceptance of Cadaveric Livers Using an Implicit Model of the Waiting List," Operations Research, INFORMS, vol. 55(1), pages 24-36, February.

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