We are interested in chance-constraints of the form P(y^ω_t + w^ω_t ≤ x_t, ∀t ∈ T) ≥ 1 − ϵ, ∀t ∈ T. Here, x and y are decisions and w denotes scenarios obtained from an unknown probability distribution. Optimizing over such a constraint is NP-hard, and such optimization models are notoriously difficult to solve computationally. We are interested in numerical algorithms that achieve provably high-quality solutions under special cases of such models.

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Bismark Singh