Adaptive optimization and systematic probing of infrastructure system maintenance policies under model uncertainty

Samer Madanat, Sejung Park, Kenneth Kuhn

    Research output: Contribution to journalArticle

    Abstract

    We present an application of systematic probing for selecting optimal maintenance, repair, and reconstruction (MR&R) policies for systems of infrastructure facilities under model uncertainty. We use an open-loop feedback control approach, where the model parameters are updated sequentially after every inspection round. The use of systematic probing improves the convergence of the model parameters by ensuring that all permissible actions are applied to every condition state. The results of the parametric analyses demonstrate that the MR&R policies converge earlier when systematic probing is used. However, the savings in the expected total costs as a result of probing are minor, and are only realized when the optimal probing fractions are used. On the other hand, the additional costs incurred when the wrong probing fractions are used are significant. The major conclusion from this work is that state-of-the-art adaptive infrastructure management systems, that do not use probing, provide sufficiently close to optimal policies.

    Original languageEnglish (US)
    Pages (from-to)192-198
    Number of pages7
    JournalJournal of Infrastructure Systems
    Volume12
    Issue number3
    DOIs
    StatePublished - Sep 1 2006

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    Reconstruction (structural)
    Feedback control
    Costs
    Repair
    Inspection
    Uncertainty

    Keywords

    • Adaptive systems
    • Infrastructure
    • Maintenance
    • Optimization
    • Probabilistic models
    • Uncertainty principles

    ASJC Scopus subject areas

    • Civil and Structural Engineering

    Cite this

    Adaptive optimization and systematic probing of infrastructure system maintenance policies under model uncertainty. / Madanat, Samer; Park, Sejung; Kuhn, Kenneth.

    In: Journal of Infrastructure Systems, Vol. 12, No. 3, 01.09.2006, p. 192-198.

    Research output: Contribution to journalArticle

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