Probabilistic Life-Cycle Cost Analysis of Pavements Based on Simulation Optimization

Abstract

Life-cycle cost analysis (LCCA) is a way to evaluate the long-term cost effectiveness of different pavement designs or treatment actions. Owing to the existence of uncertainties, many probabilistic LCCA models have been proposed. They mainly use a prescribed treatment schedule or determine schedules by mechanistic-empirical analysis, potentially leading to the overestimation of life-cycle cost (LCC). In this paper, a new probabilistic simulation-optimization LCCA model is proposed. This new model determines treatment schedules by minimizing total LCC, including agency and user cost, which is different from current probabilistic models. In addition, it also incorporates uncertainties of treatment costs and deterioration processes. Two case studies are presented. The first one shows the influence of treatment schedule uncertainties on LCC distributions. After considering treatment schedule uncertainties, a tighter LCC distribution is estimated. The second case study compares the new model and a conventional prescribed-schedule model from the perspective of pavement design selection. The results show that the simulation-optimization model could lead to different preferred pavement designs than the prescribed-schedule model.