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Accelerating Procedures of the Value Iteration Algorithm for Discounted Markov Decision Processes, Based on a One-Step Lookahead Analysis

Author

Listed:
  • Meir Herzberg

    (Telecom Australia Research Laboratories, Clayton, Victoria, Australia)

  • Uri Yechiali

    (Tel Aviv University, Tel Aviv, Israel)

Abstract

Accelerating procedures for solving discounted Markov decision processes problems are developed based on a one-step lookahead analysis of the value iteration algorithm. We apply the criteria of minimum difference and minimum variance to obtain good adaptive relaxation factors that speed up the convergence of the algorithm. Several problems (including Howard's automobile replacement) are tested and a preliminary numerical evaluation reveals considerable reductions in computation time when compared to existing value iteration schemes.

Suggested Citation

  • Meir Herzberg & Uri Yechiali, 1994. "Accelerating Procedures of the Value Iteration Algorithm for Discounted Markov Decision Processes, Based on a One-Step Lookahead Analysis," Operations Research, INFORMS, vol. 42(5), pages 940-946, October.
    • Handle: RePEc:inm:oropre:v:42:y:1994:i:5:p:940-946
    DOI: 10.1287/opre.42.5.940
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    Cited by:

    1. Herzberg, Meir & Yechiali, Uri, 1996. "A K-step look-ahead analysis of value iteration algorithms for Markov decision processes," European Journal of Operational Research, Elsevier, vol. 88(3), pages 622-636, February.
    2. George Liberopoulos & Dimitrios Pandelis & Olympia Hatzikonstantinou, 2013. "The stochastic economic lot sizing problem for non-stop multi-grade production with sequence-restricted setup changeovers," Annals of Operations Research, Springer, vol. 209(1), pages 179-205, October.
    3. Oleksandr Shlakhter & Chi-Guhn Lee & Dmitry Khmelev & Nasser Jaber, 2010. "Acceleration Operators in the Value Iteration Algorithms for Markov Decision Processes," Operations Research, INFORMS, vol. 58(1), pages 193-202, February.
    4. Oleksandr Shlakhter & Chi-Guhn Lee, 2013. "Accelerated modified policy iteration algorithms for Markov decision processes," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 78(1), pages 61-76, August.

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