Censored lifetime learning: Optimal Bayesian age-replacement policies

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7 Citations (Scopus)


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 languageEnglish
Pages (from-to)827-834
Number of pages8
JournalOperations Research Letters
Issue number6
Publication statusPublished - Nov 2020


  • Age-replacement
  • Asymptotic optimality
  • Bayesian learning
  • Censoring
  • Maintenance


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