Abstract
We suggest a heuristic solution procedure for Partially Observable Markov Decision Processes with finite action space and finite state space with infinite horizon. The algorithm is a fast, very simple general heuristic; it is applicable for multiple states (not necessarily ordered) multiple actions and various distribution functions. The quality of the algorithm is checked in this paper against existing analytical and empirical results for two specific models of machine replacement. One model refers to the case of two‐action and two‐system states with uniform observations (Grosfeld‐Nir [4]), and the other model refers to a case of many ordered states with binomial observations (Sinuany‐Stern et al. [11]). The paper also presents the model realization for various probability distribution functions applied to maintenance and quality control.
Similar content being viewed by others
References
C.S. Albright, Structural results for partially observable Markov decision processes, Oper. Res. 27(1979)1041-1053.
D.P. Bertsekas, Dynamic Programming and Stochastic Control, Academic Press, New York, 1976.
A.J. Duncan, Quality Control and Industrial Statistics, Irwin, Homewood, IL, 1986, 5th ed.
A. Grosfeld-Nir, A two-state partially observable Markov decision process with uniformly distributed observations, Oper. Res. 44(1996)458-463.
S.H. Kim and J.B. Ho, A partially observable Markov decision process with lagged information, J. Oper. Res. Soc. 38(1987)439-446.
D.E. Lane, A partially observable model of decision making for fishermen, Oper. Res. 37(1989)240-254.
W.S. Lovejoy, A survey of algorithmic methods for POMDPs, Ann. Oper. Res. 28 (1991)47-65.
W.S. Lovejoy, Computationally feasible bounds for POMDPs, Oper. Res. 39(1991)162-175.
G.E. Monahan, A survey of POMDPs: Theory, models and algorithms. Manag. Sci. 28(1982)1-16.
Z. Sinuany-Stern, Replacement policy under partially observed Markov process, Inter. J. Prod. Econ. 29(1993)159-166.
Z. Sinuany-Stern, I. David and S. Biran, An efficient heuristic for a partially observable Markov decision process of machine replacement, Computers Oper. Res. 24(1997)117-126.
C.C. White, A Markov quality control process subject to partial observation, Manag. Sci. 23(1977)843-852.
C.C. White, Optimal control limit strategies for a partially observed replacement problem, Int. J. Sys. Sci. 10(1979)321-331.
C.C. White, A survey of solution techniques for the POMDP, Ann. Oper. Res. 32(1991)215-230.
C.C. White and D.P. Harrington, Application of Jensen's inequality for adaptive suboptimal design, J. Optim. Theory Appl. 32(1980)89-99.
C.C. White and W.T. Scherer, Finite-memory suboptimal design for Partially Observed Markov Decision Processes, Oper. Res. 42(1994)439-455.
D.J. White, Real applications of Markov decision processes, Interfaces 15(1985)7-83.
D.J. White, Further real applications of Markov decision processes, Interfaces 18(1988)55-61.
Rights and permissions
About this article
Cite this article
David, I., Friedman, L. & Sinuany‐Stern, Z. A simple suboptimal algorithm for system maintenanceunder partial observability. Annals of Operations Research 91, 25–40 (1999). https://doi.org/10.1023/A:1018949723461
Published:
Issue Date:
DOI: https://doi.org/10.1023/A:1018949723461