Stochastic scenario generation: An empirical approach - Oliveira, A. D.; Filomena, T. P. (Anais do Encontro de Teoria da Computação (ETC), 2016)
We briefly discuss the differences among several methods to generate a scenario tree for stochastic optimization. First, the Monte Carlo Random sampling is presented, followed by the Fitting of the First Two Moments sampling, and lastly the Michaud sampling. Literature results are reviewed, taking into account distinctive features of each kind of methodology. According to the literature results, it is fundamental to consider the problem’s unique characteristics to make the more appropriate choice on sampling method.