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Finite horizon semi-Markov decision processes with application to maintenance systems

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  • Huang, Yonghui
  • Guo, Xianping

Abstract

This paper investigates finite horizon semi-Markov decision processes with denumerable states. The optimality is over the class of all randomized history-dependent policies which include states and also planning horizons, and the cost rate function is assumed to be bounded below. Under suitable conditions, we show that the value function is a minimum nonnegative solution to the optimality equation and there exists an optimal policy. Moreover, we develop an effective algorithm for computing optimal policies, derive some properties of optimal policies, and in addition, illustrate our main results with a maintenance system.

Suggested Citation

  • Huang, Yonghui & Guo, Xianping, 2011. "Finite horizon semi-Markov decision processes with application to maintenance systems," European Journal of Operational Research, Elsevier, vol. 212(1), pages 131-140, July.
  • Handle: RePEc:eee:ejores:v:212:y:2011:i:1:p:131-140
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    1. Çekyay, B. & Özekici, S., 2010. "Mean time to failure and availability of semi-Markov missions with maximal repair," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1442-1454, December.
    2. Singh, Sumeetpal S. & Tadic, Vladislav B. & Doucet, Arnaud, 2007. "A policy gradient method for semi-Markov decision processes with application to call admission control," European Journal of Operational Research, Elsevier, vol. 178(3), pages 808-818, May.
    3. Love, C. E. & Zhang, Z. G. & Zitron, M. A. & Guo, R., 2000. "A discrete semi-Markov decision model to determine the optimal repair/replacement policy under general repairs," European Journal of Operational Research, Elsevier, vol. 125(2), pages 398-409, September.
    4. Nielsen, Lars Relund & Kristensen, Anders Ringgaard, 2006. "Finding the K best policies in a finite-horizon Markov decision process," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1164-1179, December.
    5. Fernando Luque-Vásquez & J. Minjárez-Sosa, 2005. "Semi-Markov control processes with unknown holding times distribution under a discounted criterion," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 61(3), pages 455-468, July.
    6. Anna Jaśkiewicz, 2001. "An approximation approach to ergodic semi-Markov control processes," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 54(1), pages 1-19, October.
    7. Eugene A. Feinberg, 2004. "Continuous Time Discounted Jump Markov Decision Processes: A Discrete-Event Approach," Mathematics of Operations Research, INFORMS, vol. 29(3), pages 492-524, August.
    8. John W. Mamer, 1986. "Successive Approximations for Finite Horizon, Semi-Markov Decision Processes with Application to Asset Liquidation," Operations Research, INFORMS, vol. 34(4), pages 638-644, August.
    9. Diego Klabjan & Daniel Adelman, 2007. "An Infinite-Dimensional Linear Programming Algorithm for Deterministic Semi-Markov Decision Processes on Borel Spaces," Mathematics of Operations Research, INFORMS, vol. 32(3), pages 528-550, August.
    10. Gunter, Sevket & Swanson, Lloyd, 1987. "Semi-Markov dynamic programming approach to competitive bidding with state space reduction considerations," European Journal of Operational Research, Elsevier, vol. 32(3), pages 435-447, December.
    11. D. J. White, 1995. "Finite Horizon Markov Decision Processes with Uncertain Terminal Payoffs," Operations Research, INFORMS, vol. 43(5), pages 862-869, October.
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    Cited by:

    1. Fang Chen & Xianping Guo & Zhong-Wei Liao, 2022. "Optimal Stopping Time on Semi-Markov Processes with Finite Horizon," Journal of Optimization Theory and Applications, Springer, vol. 194(2), pages 408-439, August.
    2. Sadoghi, Amirhossein & Vecer, Jan, 2022. "Optimal liquidation problem in illiquid markets," European Journal of Operational Research, Elsevier, vol. 296(3), pages 1050-1066.
    3. Amirhossein Sadoghi & Jan Vecer, 2022. "Optimal liquidation problem in illiquid markets," Post-Print hal-03696768, HAL.
    4. Insua, David Rios & Ruggeri, Fabrizio & Soyer, Refik & Wilson, Simon, 2020. "Advances in Bayesian decision making in reliability," European Journal of Operational Research, Elsevier, vol. 282(1), pages 1-18.
    5. Sharafali, Moosa & Tarakci, Hakan & Kulkarni, Shailesh & Razack Shahul Hameed, Raja Abdul, 2019. "Optimal delivery due date for a supplier with an unreliable machine under outsourced maintenance," International Journal of Production Economics, Elsevier, vol. 208(C), pages 53-68.
    6. Antoine Jacquier & Hao Liu, 2017. "Optimal liquidation in a Level-I limit order book for large tick stocks," Papers 1701.01327, arXiv.org, revised Nov 2017.

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