Optimization algorithms can exploit problem structures of various kinds, such as sparsity of derivatives, complementarity conditions, block structure, stochasticity, priorities for discrete variables, and information about piecewiselinear terms. Moreover, some algorithms deduce additional structural information that may help the modeler. We review and discuss some ways of conveying structure, w...

We introduce an algebraic modeling language, named ROME, for a class of robust optimizationproblems. ROME serves as an intermediate layer between the modeler and optimization solverengines, allowing modelers to express robust optimization problems in a mathematically meaningfulway. In this paper, we highlight key features of ROME which expediates the modeling and subsequentnumer...