Modeling the Optimal Maintenance Scheduling Strategy for Bridge Networks

Abstract

An optimal maintenance scheduling strategy for bridge networks can generate an efficient allocation of resources with budget limits and mitigate the perturbations caused by maintenance activities to the traffic flows. This research formulates the optimal maintenance scheduling problem as a bi-level programming model. The upper-level model is a multi-objective nonlinear programming model, which minimizes the total traffic delays during the maintenance period and maximizes the number of bridges to be maintained subject to the budget limit and the number of crews. In the lower-level, the users’ route choice following the upper-level decision is simulated using a modified user equilibrium model. Then, the proposed bi-level model is transformed into an equivalent single-level model that is solved by the simulated annealing algorithm. Finally, the model and algorithm are tested using a highway bridge network. The results show that the proposed method has an advantage in saving maintenance costs, reducing traffic delays, minimizing makespan compared with two empirical maintenance strategies. The sensitivity analysis reveals that traffic demand, number of crews, availability of budget, and decision maker’s preference all have significant effects on the optimal maintenance scheduling scheme for bridges including time sequence and job sequence.

365‐day sectional work zone schedule optimization for road networks considering economies of scale and user cost

“…Lee et al (2016) assessed multiple types of budget and greenhouse gas emission constraints and used a bilevel solution method, wherein the lower level was solved by dynamic programming, while the upper level was fixed by a Lagrangian dual. Mao et al (2020) introduced a repair schedule problem for a bridge network and utilized a bilevel solution method, wherein the lower traffic assignment problem was solved by existing methods, while the upper repair schedule problem was addressed by simulated annealing. Guo et al (2020) considered the cost uncertainty, path dependence, and budget constraint of the entire road network and used a bilevel-like solution method, which was a two-stage bottom-up method, to solve the problem.…”

Optimal maintenance period and maintenance sequence planning under imperfect maintenance

“…The optimization problem about the losses turns into a maintenance sequence planning issue. Mao et al 32 . considered the optimal maintenance scheduling problem as a bi‐level programming model, and the proposed bi‐level model was transformed into an equivalent single‐level model.…”

Integrative Evolutionary-Based Method for Modeling and Optimizing Budget Assignment of Bridge Maintenance Priorities

“…Genetic algorithm was applied to find the optimal maintenance plans by accommodating the performance requirements and tight budget constraints. Mao et al (2020) designed an optimal maintenance scheduling strategy that was formulated in the form of two levels. The upper level incorporated a multi-objective non-linear programming model, which aimed at minimizing the total traffic delays during the maintenance period and maximizing the total number of bridges to be repaired.…”

“…The urgency scale was defined according to the physical condition of the bridge deck while the total prioritization scale was constructed as a result of integration of the normalized values of performance, economic and criticality scales. It is worth mentioning that most of the prioritization and maintenance optimization models are deterministic and don't model the inherent uncertainties of the construction process, which usually don't lead to optimal solutions (Mao et al, 2020;Wu et al, 2017). Also, some of the maintenance prioritization models were mainly driven by preferences of domain experts and subjective rankings, which may not be necessarily applicable to be generalized to be applied elsewhere (Safa et al, 2014;Jahan et al, 2012).…”