Abstract
We consider a sequence of age-replacement problems with a general lifetime distribution parametrized by an a-priori unknown parameter. There is a trade-off: Preventive replacements are censored but cheap, whereas corrective replacements are uncensored but costly observations of the lifetime distribution. We first analyze the optimal policy for a finite sequence and establish some properties. We then propose a myopic Bayesian policy that almost surely learns the unknown parameter and converges to the optimal policy with full knowledge of the parameter.
Original language | English |
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Pages (from-to) | 827-834 |
Number of pages | 8 |
Journal | Operations Research Letters |
Volume | 48 |
Issue number | 6 |
DOIs | |
Publication status | Published - Nov 2020 |
Keywords
- Age-replacement
- Asymptotic optimality
- Bayesian learning
- Censoring
- Maintenance