Mathematical optimization

Econometrics

Economics

Metric (unit)

Stochastic optimization

Operations management

Wasserstein metric

Applied mathematics

Mathematics

Computer science

Operations Research Letters

In this paper, we study a data-driven risk-averse stochastic optimization approach with Wasserstein Metric for the general distribution case. By using the Wasserstein Metric, we can successfully reformulate the risk-averse two-stage stochastic optimization problem with distributional ambiguity to a traditional two-stage robust optimization problem. In addition, we derive the worst-case distribution and perform convergence analysis to show that the risk aversion of the proposed formulation vanishes as the size of historical data grows to infinity.

Data-driven risk-averse stochastic optimization with Wasserstein metric