Optimisation framework that explicitly represents uncertainty using scenarios or probability distributions.
Stochastic programming models decisions in the presence of uncertainty, for example uncertain inflows, fuel prices or demand. Typical formulations use a set of scenarios with associated probabilities and aim to find decisions that perform well on average or minimise expected cost while controlling risk measures. It complements deterministic planning runs.
