SDDP for multistage stochastic programs: preprocessing via scenario reduction

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10385102" target="_blank" >RIV/00216208:11320/17:10385102 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/s10287-016-0261-6" target="_blank" >https://doi.org/10.1007/s10287-016-0261-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10287-016-0261-6" target="_blank" >10.1007/s10287-016-0261-6</a>

Result language
angličtina
Original language name
SDDP for multistage stochastic programs: preprocessing via scenario reduction
Original language description
Even with recent enhancements, computation times for large-scale multistage problems with risk-averse objective functions can be very long. Therefore, preprocessing via scenario reduction could be considered as a way to significantly improve the overall performance. Stage-wise backward reduction of single scenarios applied to a fixed branching structure of the tree is a promising tool for efficient algorithms like stochastic dual dynamic programming. We provide computational results which show an acceptable precision of the results for the reduced problem and a substantial decrease of the total computation time.
Czech name
—
Czech description
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Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Project
<a href="/en/project/GBP402%2F12%2FG097" target="_blank" >GBP402/12/G097: DYME-Dynamic Models in Economics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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