Adaptive Optimization of Infrastructure Maintenance and Inspection Decisions under Performance Model Uncertainty
Publication: Journal of Infrastructure Systems
Volume 9, Issue 4
Abstract
We present an adaptive optimization model to find joint inspection and maintenance policies for infrastructure facilities under performance model uncertainty. The objective in the formulation is to minimize the total expected social cost of managing facilities over a finite planning horizon. Recent optimization models account for the uncertainty in the selection of facility performance models through an adaptive control approach. In this paper, we relax the assumptions of fixed and error-free inspections. We present a parametric study to analyze the effect of initial performance model uncertainty and bias on the expected total cost of managing a facility. The main observation is that reducing the initial variance in model uncertainty may be more important than reducing the initial bias. Our study also shows that cost savings can result from relaxing the constraint of a fixed inspection schedule.
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References
Carnahan, J. V.(1988). “Analytical framework for optimizing pavement maintenance.” J. Transp. Eng., 114(3), 307–322.
Carnahan, J. V., Davis, W. J., Shahin, M. Y., Keane, P. L., and Wu, M. I.(1987). “Optimal maintenance decisions for pavement management.” J. Transp. Eng., 113(5), 554–572.
Durango, P. (2002). “Adaptive optimization models for infrastructure management.” PhD thesis, Univ. of California, Berkeley, Calif.
Durango, P., and Madanat, S.(2002). “Optimal maintenance and repair policies in infrastructure management under uncertain facility deterioration rates: An adaptive control approach.” Transp. Res. Part A: Policy Pract., 36, 763–778.
Humplick, F.(1992). “Highway pavement distress evaluation: Modeling measurement error.” Transp. Res., Part B: Methodol., 26, 135–154.
Klein, M.(1962). “Inspection-maintenance-replacement schedules under Markovian deterioration.” Manage. Sci., 9, 25–32.
Madanat, S.(1993a). “Incorporating inspection decisions in pavement management.” Transp. Res., Part B: Methodol., 27(6), 425–438.
Madanat, S.(1993b). “Optimal infrastructure management decisions under uncertainty.” Transp. Res., Part C: Emerg. Technol., 1(1), 77–88.
Madanat, S., and Ben-Akiva, M.(1994). “Optimal inspection and repair policies for infrastructure facilities.” Transp. Sci., 28(1), 55–61.
Madanat, S., and Wan Ibrahim, W. H.(1995). “Poisson regression models of infrastructure transition probabilities.” J. Transp. Eng., 121(3), 267–272.
Mine, H., and Kawai, H. (1982). “An optimal inspection and maintenance policy of a deteriorating system.” J. Oper. Res. Soc. Jpn., 25(1).
Mishalani, R., and Madanat, S.(2002). “Computation of infrastructure transition probabilities using stochastic duration models.” J. Infrastruct. Syst., 8(4), 139–148.
Olsonen, R. (1988). “Finland’s pavement management system: Data and models for the condition of roads.” Rep., Finnish Roads and Waterways Administration, Helsinki, Finland.
Smilowitz, K., and Madanat, S.(2000). “Optimal inspection, maintenance and rehabilitation policies for networks of infrastructure facilities under measurement and forecasting uncertainty.” J. Comput.-Aided Civ. Infrastruct. Eng., 15(1), 5–13.
Information & Authors
Information
Published In
Journal of Infrastructure Systems
Volume 9 • Issue 4 • December 2003
Pages: 133 - 139
Copyright
Copyright © 2003 American Society of Civil Engineers.
History
Received: Sep 4, 2002
Accepted: Jun 10, 2003
Published online: Nov 14, 2003
Published in print: Dec 2003
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