Censored lifetime learning: Optimal Bayesian age-replacement policies

Research output: Contribution to journalArticleAcademicpeer-review

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 languageEnglish
Pages (from-to)827-834
Number of pages8
JournalOperations Research Letters
Volume48
Issue number6
DOIs
Publication statusPublished - Nov 2020

Keywords

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

Fingerprint Dive into the research topics of 'Censored lifetime learning: Optimal Bayesian age-replacement policies'. Together they form a unique fingerprint.

Cite this