Road network sustainability: a scenario-based approach to maintenance & rehabilitation planning

The present research develops a robust network-level pavement maintenance and rehabilitation (M&R) planning model with uncertainties of pavement condition and the available budget. It uses Mulvey robust optimization methodology and incorporates the uncertainty in the mathematical formulation to determine an M&R plan which works in every possible situation. Pavement Condition Index (PCI) is employed for modelling of pavement performance and the M&R decisions are then determined to satisfy minimum pavement conditions and budget constraints. The proposed robust model is solved by Mix-integer programming (MIP) through a case study, and its results are compared with those obtained from a deterministic model. The results show that the robust approach stays valid over a range of pavement condition and budget variables, while maintaining the required minimum pavement condition across the network. While the deterministic model provides only one solution of the optimal plan with the minimum cost of 19500 IRR, the developed model provides a near-optimal plan without considerable sensitivity to changes in uncertain parameters. These findings demonstrate the potential of Mulvey robust optimization approach for developing more reliable network-level pavement M&R strategies under uncertainty.