Adaptive Optimization and Systematic Probing of Infrastructure System Maintenance Policies under Model Uncertainty
Publication: Journal of Infrastructure Systems
Volume 12, Issue 3
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.
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Acknowledgments
Partial funding for this research was provided by a University of California Transportation Center (UCTC) research grant to the first writer. The writers benefitted from discussions with Carlos Daganzo. The comments of two anonymous referees were instrumental in improving the quality of this paper.
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Information & Authors
Information
Published In
Journal of Infrastructure Systems
Volume 12 • Issue 3 • September 2006
Pages: 192 - 198
Copyright
© 2006 ASCE.
History
Received: May 6, 2004
Accepted: Apr 19, 2006
Published online: Sep 1, 2006
Published in print: Sep 2006
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