Robust Facility Location Problem Under Uncertainty

In this thesis we consider a multi-period fixed-charge facility location problem under uncertainty in demand to which we apply a robust optimization approach. We use a two-stage approach where in the first stage the locations and the capacities of the facilities to be opened are determined. These decisions are then tested in the second stage where the production and allocation of products are determined. We make use of sample paths, where the customers’ demand is sampled over an uncertainty set. We consider this uncertain demand to be bounded within a multidimensional box. We show that the robust approach can provide improvements in the objective when partially immunizing against the uncertainty.