Risk-averse Oil-spill Response Planning

Abstract

Extensive reliance on marine oil transportation imposes significant risks to local environments, economies, and local communities across the globe. To improve preparedness against the imposed risks, this paper develops a risk-averse two-stage stochastic mixed-integer linear programming model with Conditional Value-at-Risk (CVaR) as a risk measure to optimize response activities to the oil spills. The use of CVaR allows the decision makers of oil-spill response to incorporate different risk attitudes when making relevant response decisions. Through numerical analyses, this paper shows that the risk attitude of the decision makers plays a critical role in determining the optimal oil-spill response activities.