First, three approaches to scenario generation besides Monte Carlo methods are considered: (i) Optimal quantization of probability distributions, (ii) Quasi-Monte Carlo methods and (iii) Quadrature rules based on sparse grids. The available theory is discussed and related to applying them in stochastic programming. Second, the problem of optimal scenario reduction and the generation of scenario trees for multistage models are addressed.