Risk-Aware Stochastic Ship Routing using Conditional Value-at-Risk

Improving the safety and efficiency of maritime shipping has the potential to reduce carbon emissions and improve profitability. Stochastic ship routing, the problem of finding a safe, efficient, and timely route for a ship is difficult in large part because of uncertainty in weather forecasts, which come as an ensemble, a collection of many possible future weather conditions. Previous safety-aware ship routing methods have used either conservative interpretations of the ensemble by assuming the worst-case weather conditions, leading to excessive fuel consumption, or by using the average weather conditions, leading to potentially unsafe routes. In this paper, we investigate the use of the well-known Conditional Value-at-risk (CVaR) in the objective and constraint functions for ship routing problems, which allows a range of risk tolerances between the average and the worst case. We illustrate the advantages of using CVaR for the problem of ship routing in several simulation examples using real weather forecasts.