|edoc-Server der Humboldt-Universität zu Berlin|
Kjetil Høyland, Gjensidige Nor Asset Management|
Michal Kaut, Norwegian University of Science and Technology
Stein W. Wallace, Molde University College
|Title:||A heuristic for generating scenario trees for multistage decision problems|
|Date of Acceptance:||06.04.2001|
Stochastic Programming E-Print Series |
|Editors:||Julie L. Higle; Werner Römisch; Surrajeet Sen|
|Keywords (eng):||stochastic programming, scenario tree generation, heuristics, Cholesky decomposition|
Computational Optimization and ApplicationsComputational optimization and applications : an international journal 2-3 (Vol. 24, 2003)
Springer Science + Business Media B.V. (New York, NY [u.a.])
|Metadata export: To export the complete metadata set as Endote or Bibtex format please click to the appropriate link.||Endnote Bibtex|
|In stochastic programming models we always face the problem of how to represent the random variables. This is particularly difficult with multidimensional distributions. We present an algorithm that produces a discrete joint distribution consistent with specified values of the first four marginal moments and correlations. The joint distribution is constructed by decomposing the multivariate problem into univariate ones, and using an iterative procedure that combines simulation, Cholesky decomposition and various transformations to achieve the correct correlations without changing the marginal moments. With the algorithm, we can generate 1000 one-period scenarios for 12 random variables in 16 seconds, and for 20 random variables in 48 seconds, on a Pentium III machine.|
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