A multi-year pavement maintenance program using a stochastic simulation-based genetic algorithm approach

The objective of this paper is to introduce a multi-year pavement maintenance programming methodology that can explicitly account for uncertainty in pavement deterioration. This is accomplished with the development of a simulation-based genetic algorithm (GA) approach that is capable of planning the maintenance activities over a multi-year planning period. A stochastic simulation is used to simulate the uncertainty of future pavement conditions based on the calibrated deterioration model while GA is used to handle the combinatorial nature of the network-level pavement maintenance programming. The effects of the uncertainty of pavement deterioration on the maintenance program are investigated using a case study. The results show that programming the maintenance activities using only the expected pavement conditions is likely to underestimate the required maintenance budget and overestimate the performance of pavement network.