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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Condition-Based Multiobjective Maintenance Decision Making for Highway Bridges Considering Risk Perceptions
Journal of Management in EngineeringApril 2015
Journal of Performance of Constructed FacilitiesJanuary 2013
Multiobjective Maintenance Planning Optimization for Deteriorating Bridges Considering Condition, Safety, and Life-Cycle Cost
Journal of Transportation EngineeringAugust 2013
Postdoctoral Research Associate, Dept. of Civil and Environmental Engineering, ATLSS Engineering Research Center, Lehigh Univ., 117 ATLSS Dr., Bethlehem, PA 18015-4729.
Received: October 19, 2018
Accepted: September 03, 2019
Published online: February 19, 2020
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