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Computing optimal quality control policies — two actions

Published online by Cambridge University Press:  14 July 2016

Robert C. Wang
Robert C. Wang*
Affiliation:
Mountain States Telephone and Telegraph Company (Montain Bell), Denver, Colorado
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Abstract

We study a Markov quality control model in which we may either reset the machine or keep the machine producing items. Both discounted and average costs are considered. We shall show that a monotone policy is optimal and show how to compute the optimal critical point. Two special models are studied along with some numerical results.

Keywords

MARKOV QUALITY CONTROLDYNAMIC PROGRAMMING MONOTONE POLICYOPTIMAL CRITICAL POINT

Information

Type
Short Communications
Information
Journal of Applied Probability , Volume 13 , Issue 4 , December 1976, pp. 826 - 832
Copyright
Copyright © Applied Probability Trust 1976 

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References

Blackwell, D. (1965) Discounted dynamic programming. Ann. Math. Statist. 36, 226–235.CrossRefGoogle Scholar
Ross, S. (1968) Arbitrary state Markovian decision processes. Ann. Math. Statist. 39, 2118–2122.Google Scholar
Ross, S. (1970) Applied Probability Models with Optimization Applications. Holden-Day, San Francisco.Google Scholar
Strauch, R. (1966) Negative dynamic programming. Ann. Math. Statist. 37, 871–890.CrossRefGoogle Scholar
Wang, R. C. (1976) Computing optimal replacement policies. To appear.Google Scholar