Robust Optimization is a mathematical approach to decision-making under uncertainty, designed to find solutions that remain effective across a range of possible scenarios. It emphasizes stability and performance by incorporating uncertainty directly into the optimization model, ensuring solutions are feasible and optimal even in the worst-case scenarios.