• search hit 1 of 4
Back to Result List

On the algorithmic solution of optimization problems subject to probabilistic/robust (probust) constraints

Submission Status:Appeared online
  • We present an adaptive grid refinement algorithm to solve probabilistic optimization problems with infinitely many random constraints. Using a bilevel approach, we iteratively aggregate inequalities that provide most information not in a geometric but in a probabilistic sense. This conceptual idea, for which a convergence proof is provided, is then adapted to an implementable algorithm. The efficiency of our approach when compared to naive methods based on uniform grid refinement is illustrated for a numerical test example as well as for a water reservoir problem with joint probabilistic filling level constraints.

Download full text files

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Holger Berthold, Holger Heitsch, René Henrion, Jan Schwientek
DOI:https://doi.org/10.1007/s00186-021-00764-8
Document Type:Article
Language:English
Date of Publication (online):2021/05/13
Release Date:2021/05/13
Tag:bilevel optimization; chance constraints; probabilistic constraints; probust constraints; semi-infinite optimization
Institutes:Weierstraß-Institut für Angewandte Analysis und Stochastik
Subprojects:B04
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International