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Contextual Distributionally Robust Chance-Constrained Programs: Exact Reformulations and Valid Inequalities
We study a contextual distributionally robust chance-constrained programming (C-DRCCP) model that controls violation probabilities conditional on a neighborhood of a target context. The ambiguity set is defined over the joint distribution of contexts and outcomes using the Wasserstein distance. For
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