Stochastic scenario generation: An empirical approach

  • A. D. Oliveira UFRGS
  • T. P. Filomena UFRGS

Resumo


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.


 

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Publicado
04/07/2016
OLIVEIRA, A. D.; FILOMENA, T. P.. Stochastic scenario generation: An empirical approach. In: ENCONTRO DE TEORIA DA COMPUTAÇÃO (ETC), 1. , 2016, Porto Alegre. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2016 . p. 883-886. ISSN 2595-6116. DOI: https://doi.org/10.5753/etc.2016.9851.