View article

Robust optimization is an emerging approach in integer programming taking data uncertainty into account. Recently, the adjustable Γ-robustness approach of Bertsimas and Sim [3, 4] has been applied to network design problems. In this paper, we consider this so-called Γ-robust network design problem. We investigate its polyhedral structure and present robust versions of the cutset inequalities as well as computational results on their effectiveness.