Distributionally Robust Convex Optimization

@article{Wiesemann2014DistributionallyRC,
  title={Distributionally Robust Convex Optimization},
  author={Wolfram Wiesemann and Daniel Kuhn and Melvyn Sim},
  journal={Operations Research},
  year={2014},
  volume={62},
  pages={1358-1376}
}
Distributionally robust optimization is a paradigm for decision-making under uncertainty where the uncertain problem data is governed by a probability distribution that is itself subject to uncertainty. The distribution is then assumed to belong to an ambiguity set comprising all distributions that are compatible with the decision maker’s prior information. In this paper, we propose a unifying framework for modeling and solving distributionally robust optimization problems. We introduce… CONTINUE READING
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