Robust optimization is an area of mathematical programming that generates solutions which are feasible for any realization of uncertain parameters within a given uncertainty set. In this thesis, a specific approach of robust optimization, the price of robustness by D. Bertsimas and M. Sim, is applied to the real world problem of scheduling the handling of outbound baggage and assigning flights to baggage carousels at Terminal 2 of Munich Airport. A robust optimization model is derived and evaluated by a CPLEX implementation and a simulation study. It is shown that the complexity of the model remains in the class of mixed integer linear programs even if robustness is enforced. Another major finding is that, in most cases, it is not necessary to enforce full robustness and that low degrees of robustness are sufficient for the benefits of robust solutions. This is especially advantageous in scenarios with scarce resources.     «

Robust optimization is an area of mathematical programming that generates solutions which are feasible for any realization of uncertain parameters within a given uncertainty set. In this thesis, a specific approach of robust optimization, the price of robustness by D. Bertsimas and M. Sim, is applied to the real world problem of scheduling the handling of outbound baggage and assigning flights to baggage carousels at Terminal 2 of Munich Airport. A robust optimization model is derived and evalua...     »