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Discounted Markov Programming in a Periodic Process

Author

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  • Jens Ove Riis

    (Danmarks Tekniske Højskole, Copenhagen, Denmark)

Abstract

This paper deals with a nonstationary discrete-time Markov process whose transition probabilities vary periodically in time. Each transition results in a reward that varies within the same cycle as the transition matrix. For infinite processes a policy-iteration algorithm is developed that effectively determines an optimal policy maximizing the total discounted reward. The paper represents an extension of R. A. Howard's policy-iteration technique for stationary Markov processes. A numerical example is given in which the developed iteration algorithm is demonstrated.

Suggested Citation

  • Jens Ove Riis, 1965. "Discounted Markov Programming in a Periodic Process," Operations Research, INFORMS, vol. 13(6), pages 920-929, December.
    • Handle: RePEc:inm:oropre:v:13:y:1965:i:6:p:920-929
    DOI: 10.1287/opre.13.6.920
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    Cited by:

    1. Sun, Bo & Sun, Xu & Tsang, Danny H.K. & Whitt, Ward, 2019. "Optimal battery purchasing and charging strategy at electric vehicle battery swap stations," European Journal of Operational Research, Elsevier, vol. 279(2), pages 524-539.
    2. Horowitz, Uri, 1974. "A dynamic model integrating demand and supply relationships for agricultural water, applied to determining optimal intertemporal allocation of water in a regional water project," ISU General Staff Papers 197401010800006990, Iowa State University, Department of Economics.
    3. Aknouche, Abdelhakim, 2024. "Periodically homogeneous Markov chains: The discrete state space case," MPRA Paper 122287, University Library of Munich, Germany.

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