ROC++: Robust Optimization in C++

Understand

Robust optimization is a very popular means to address decision-making problems affected by uncertainty.

• Its success has been fueled by its attractive robustness and scalability properties, by ease of modeling, and by the limited assumptions it needs about the uncertain parameters to yield meaningful solutions.
• Robust optimization techniques can address both single- and multi-stage decision-making problems involving real-valued and/or binary decisions, and exogenous and/or endogenous uncertain parameters.
• Many of these techniques apply to problems with either robust (worst-case) or stochastic (expectation) objectives and can thus be tailored to the risk preferences of the decision-maker.