OPTIMAL INSPECTION AND REPAIR POLICIES FOR INFRASTRUCTURE FACILITIES

State-of-the-art decision-making models in the area of infrastructure maintenance and rehabilitation (which are based on the Markov Decision Process) do not take into account the uncertainty in the measurement of facility condition. This paper presents a methodology, the Latent M arkov Decision Process (LMDP), which explicitly recognizes the presenc e of random errors in the measurement of the condition of infrastructu re facilities. Two versions of the LMDP are presented. In the first ve rsion, the inspection schedule is fixed, which is the usual assumption made in state-of-the-art models. The second version of the LMDP minim izes the sum of inspection and M & R costs. An empirical comparison of the two versions of the LMDP and the traditional MDP illustrates the importance of incorporating measurement uncertainty in decision-making and of optimizing the inspection schedule.