Article ID: | iaor2003542 |
Country: | United Kingdom |
Volume: | 36A |
Issue: | 6 |
Start Page Number: | 525 |
End Page Number: | 536 |
Publication Date: | Jul 2002 |
Journal: | Transportation Research. Part A, Policy and Practice |
Authors: | Madanat Samer, Li Yuwei |
Keywords: | markov processes, transportation: road, optimization, maintenance, repair & replacement |
This paper presents a solution approach for the problem of optimising the frequency and intensity of pavement resurfacing, under steady-state conditions. If the pavement deterioration and improvement models are deterministic and follow the Markov property, it is possible to develop a simple but exact solution method. This method removes the need to solve the problem as an optimal control problem, which had been the focus of previous research in this area. The key to our approach is the realisation that, at optimality, the system enters the steady state at the time of the first resurfacing. The optimal resurfacing strategy is to define a minimum serviceability level (or maximum roughness level), and whenever the pavement deteriorates to that level, to resurface with a fixed intensity. The optimal strategy does not depend on the initial condition of the pavement, as long as the initial condition is better than the condition that triggers resurfacing. This observation allows us to use a simple solution method. We apply this solution procedure to a case study, using data obtained from the literature. The results indicate that the discounted lifetime cost is not very sensitive to cycle time. What matters most is the best achievable roughness level. The minimum serviceability level strategy is robust in that when there is uncertainty in the deterioration process, the optimal condition that triggers resurfacing is not significantly changed.