ROmodel: modeling robust optimization problems in Pyomo

Abstract This paper introduces ROmodel, an open source Python package extending the modeling capabilities of algebraic language Pyomo to robust optimization problems. ROmodel helps practitioners transition from deterministic through objects which allow formulating models in close analogy their mathematical formulation. contains a library commonly used uncertainty sets can be generated using matrix representations, but it also allows users define custom constraints. supports adjustable variables via linear decision rules. The resulting solved ROmodels solvers implement both reformulation and cutting plane approach. is platform compare reformulations. We demonstrate ROmodel’s by applying six case studies. based on (warped) Gaussian processes show how integrate data-driven with optimization.