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Linear Programming Solutions for Separable Markovian Decision Problems

Author

Listed:
  • Guy T. de Ghellinck

    (University of Louvain, Louvain, Belgium)

  • Gary D. Eppen

    (University of Chicago)

Abstract

This paper is concerned with the linear programming solutions to sequential decision (or control) problems in which the stochastic element is Markovian and in which the objective is to minimize the discounted sum of expected costs when a discount factor \lambda, 0 \leqq \lambda 2 ) of variables than the usual formulation of these problems. Two well-known example problems are solved to illustrate the wide applicability and the utility of these results.

Suggested Citation

  • Guy T. de Ghellinck & Gary D. Eppen, 1967. "Linear Programming Solutions for Separable Markovian Decision Problems," Management Science, INFORMS, vol. 13(5), pages 371-394, January.
    • Handle: RePEc:inm:ormnsc:v:13:y:1967:i:5:p:371-394
    DOI: 10.1287/mnsc.13.5.371
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    Cited by:

    1. Lodewijk Kallenberg, 2013. "Derman’s book as inspiration: some results on LP for MDPs," Annals of Operations Research, Springer, vol. 208(1), pages 63-94, September.
    2. Chen Shaoxiang, 2004. "The Infinite Horizon Periodic Review Problem with Setup Costs and Capacity Constraints: A Partial Characterization of the Optimal Policy," Operations Research, INFORMS, vol. 52(3), pages 409-421, June.
    3. Stasko, Timon H. & Oliver Gao, H., 2012. "Developing green fleet management strategies: Repair/retrofit/replacement decisions under environmental regulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1216-1226.

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