A true single–level reformulation for pessimistic bilevel optimization

We propose a single-level reformulation (SLR) for pessimistic bilevel optimization that does not rely on complementarity conditions or optimal value functions. For this reason, we refer to it as a true single-level reformulation (tSLR). A remarkable consequence is that this formulation can satisfy the classical linear independence constraint qualification, despite the fact that even the … Read more

Robust Optimization Under Controllable Uncertainty

Applications for optimization with uncertain data in practice often feature a possibility to reduce the uncertainty at a given query cost, e.g., by conducting measurements, surveys, or paying a third party in advance to limit the deviations. To model this type of applications we introduce the concept of optimization problems under controllable uncertainty (OCU). For … Read more