Quotation Hochreiter, Ronald. 2009. Algorithmic Aspects of Scenario-Based Multi-stage Decision Process Optimization. Lecture Notes in Computer Science 5783 365-376.




Multi-stage decision optimization under uncertainty depends on a careful numerical approximation of the underlying stochastic process, which describes the future uncertain values on which the decision will depend on. The quality of the scenario model severely affects the quality of the solution of the optimization model. Various approaches towards an optimal generation of discrete-state approximations (represented as scenario trees) have been suggested in the literature. Direct scenario tree sampling based on historical data or econometric models, as well as scenario path simulation and optimal tree approximation methods are discussed from an algorithmic perspective. A multi-stage financial asset management decision optimization model is presented to outline strategies to analyze the impact of various algorithmic scenario generation methodologies.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Lecture Notes in Computer Science (LNCS)
WU-Journal-Rating new STRAT-C
Language English
Title Algorithmic Aspects of Scenario-Based Multi-stage Decision Process Optimization
Volume 5783
Year 2009
Page from 365
Page to 376
Reviewed? Y
URL http://dx.doi.org/10.1007/978-3-642-04428-1_32


Hochreiter, Ronald (Details)
Institute for Statistics and Mathematics IN (Details)
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