Budgeting maintenance dredging projects under uncertainty to improve the inland waterway network performance

We model the problem of budgeting and selecting inland maintenance dredging projects to maximize the value of commodities that can be transported without disruption through the inland waterway system. We develop a heuristic to solve our stochastic optimization model and demonstrate that, by incorporating uncertainty in the amount of reactive (i.e., emergency) dredging, our model yields improved solutions as compared to related deterministic optimization models in the literature. We apply our model to provide a detailed analysis of U.S. waterway network.