Condition-Based Multiobjective Maintenance Decision Making for Highway Bridges Considering Risk Perceptions
Publication: Journal of Structural Engineering
Volume 146, Issue 5
Abstract
This paper proposes a novel optimal condition-based life-cycle highway bridge maintenance framework incorporating decision makers’ risk perceptions. The inspection and repair planning are formulated as a multiobjective optimization problem, i.e., simultaneously minimizing the expected maintenance cost and expected failure cost. Monte Carlo simulation is employed to calculate the distribution of maintenance and failure costs. To be consistent with bridge maintenance practices, both preventative and essential maintenance are considered, where the maintenance action is dependent on the load rating factor of individual bridge components. Utility theory and cumulative prospect theory are used to model decision makers’ risk preference among the Pareto front solutions. The cost-benefit implications of the Pareto front in terms of maintenance and failure costs, in conjunction with the preference solutions provided by utility theory and cumulative prospect theory, assist in the selection of the optimal bridge maintenance solution. The developed framework is illustrated on an in-service highway bridge.
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Acknowledgments
The support by grants from the US Office of Naval Research (ONR) Award Nos. N00014-08-1-0188, N00014-12-1-0023, and N00014-16-1-2299, the National Science Foundation (NSF) Award CMMI-1537926, and the Commonwealth of Pennsylvania, Department of Community and Economic Development, through the Pennsylvania Infrastructure Technology Alliance (PITA) Awards, is gratefully acknowledged. Opinions presented in this paper are those of the authors and do not necessarily reflect the views of the sponsoring organizations.
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Published In
Journal of Structural Engineering
Volume 146 • Issue 5 • May 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Oct 19, 2018
Accepted: Sep 3, 2019
Published online: Feb 19, 2020
Published in print: May 1, 2020
Discussion open until: Jul 19, 2020
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