Split cuts for robust mixed‐integer optimization

Robust optimization problems are conventionally solved by reformulation as non‐robust problems. We propose a direct method to separate split cuts for robust mixed‐integer programs with polyhedral uncertainty sets. The method generalizes the well‐known cutting plane procedure of Balas. Computational experiments show that applying cutting planes directly is favorable to the reformulation approach. It is thus viable to solve robust MIP problems in a branch‐and‐cut framework using a generalized linear programming oracle.