Evacuation Under Data Uncertainty: Robust Linear Programming Model

This paper considers evacuation via surface transportation networks in an uncertain environment. The authors focus on uncertainty associated with significant infeasibility cost in evacuation, where loss of life or property may appear. In particular, the authors flexibly change the impact of infeasibility in the form of penalty function. We develop a robust linear programming model based on a robust optimization approach. The authors show that the robustness in evacuation is important and a robust solution may outperform a nominal deterministic solution in both quality and feasibility.