An efficient heuristic for a partially observable Markov decision process of machine replacement

An efficient heuristic for a partially observable Markov decision process of machine replacement

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Article ID: iaor19972262
Country: United Kingdom
Volume: 24
Issue: 42
Start Page Number: 117
End Page Number: 126
Publication Date: Feb 1997
Journal: Computers and Operations Research
Authors: , ,
Keywords: markov processes, heuristics
Abstract:

There is, so far, only limited practical experience applying solution schemes for real-life partially observable Markov decision processes (POMDP’s). In this work the authors address the special-case POMDP associated with the famous machine-replacement problem. The machine deteriorates down a series of states according to known transition probabilities. A state is identified by a probability of producing a defective item. Only a sample of the produced items is observable at each stage, in which it is to be decided whether to replace the machine or not. The authors suggest a very simple heuristic decision-rule that can easily handle replacement-type problems of large size and which is based on the Howard solution of the fully observable version of the problem. By a simulation experimental design they compare the performance of this heuristic relative to the generic POMDP solution algorithm which has been proposed by Lovejoy.

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