Orateur
Welington de Oliveira
(Mines Paris PSL)
Description
In this talk, we address joint chance-constrained optimization problems where the only uncertain parameter is the right-hand side coefficients in an inequality system. By leveraging one-dimensional marginals, we construct nonlinear cuts that accurately approximate the probability function, which need not be differentiable or satisfy generalized concavity properties. These cuts are integrated into a proximal-like algorithm, defining iterates as stationary points of a nonlinear master program that can be solved using standard nonlinear programming solvers. Numerical experiments demonstrate the potential of our approach compared to traditional techniques that employ (sub)gradient linearizations.
Author
Welington de Oliveira
(Mines Paris PSL)
