Benchmark Instances for Robust Combinatorial Optimization with Budgeted Uncertainty

We provide test instances for robust combinatorial optimization under budget uncertainty that have been described and used for benchmarking in the paper "A Branch & Bound Algorithm for Robust Binary Optimization with Budget Uncertainty", published in Mathematical Programming Computation by Christina Büsing, Timo Gersing and Arie Koster. The set primarily consists of nominal problems from the MIPLIB 2017 that have been converted into robust problems. Furthermore, we also provide instances of the robust knapsack problem. For algorithms solving these problems see: https://doi.org/10.5281/zenodo.746337