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One-Step Improvement Ideas and Computational Aspects

In: Markov Decision Processes in Practice

Author

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  • Henk Tijms

    (Vrije Universiteit Amsterdam)

Abstract

In this contribution we give a down-to-earth discussion on basic ideas for solving practical Markov decision problems. The emphasis is on the concept of the policy-improvement step for average cost optimization. This concept provides a flexible method of improving a given policy. By appropriately designing the policy-improvement step in specific applications, tailor-made algorithms may be developed to generate the best control rule within a class of control rules characterized by a few parameters. Also, in decision problems with an intractable multi-dimensional state space, decomposition and a once-only application of the policy-improvement step may lead to a good heuristic rule. These useful features of the policy-improvement concept will be illustrated with a queueing control problem with variable service rate and with the dynamic routing of arrivals to parallel queues. In the final section, we deal with the concept of the one-stage-look-ahead rule in optimal stopping and give several applications.

Suggested Citation

  • Henk Tijms, 2017. "One-Step Improvement Ideas and Computational Aspects," International Series in Operations Research & Management Science, in: Richard J. Boucherie & Nico M. van Dijk (ed.), Markov Decision Processes in Practice, chapter 0, pages 3-32, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-47766-4_1
    DOI: 10.1007/978-3-319-47766-4_1
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