Listar por tema "Wasserstein metric"
Mostrando ítems 1-3 de 3
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Data-driven distributionally robust optimization with Wasserstein metric, moment conditions and robust constraints
(2018-07-12)We consider optimization problems where the information on the uncertain parameters reduces to a finite data sample. Using the Wasserstein metric, a ball in the space of probability distributions centered at the empirical ... -
Distributionally Robust Optimal Power Flow with Contextual Information
(Elsevier B. V., 2022-10)In this paper, we develop a distributionally robust chance-constrained formulation of the Optimal Power Flow problem (OPF) whereby the system operator can leverage contextual information. For this purpose, we exploit an ... -
Partition-based distributionally robust optimization via optimal transport with order cone constraints
(Springer, 2021)In this paper we wish to tackle stochastic programs affected by ambiguity about the probability law that governs their uncertain parameters. Using optimal transport theory, we construct an ambiguity set that exploits the ...