We introduce a new algorithmic framework for solving nonconvex optimization problems, that is called nested alternating minimization, which aims at combining the classical alternating minimization …
We propose a new data-driven approach for addressing multistage stochastic linear optimization problems with unknown distributions. The approach consists of solving a robust optimization problem th…
We investigate a simple approximation scheme, based on overlapping linear decision rules, for solving data-driven two-stage distributionally robust optimization problems with the type-∞ Wasserste…