On the algorithmic solution of optimization problems subject to probabilistic/robust (probust) constraints
Loading...
Date
2021
Volume
96
Issue
Journal
Mathematical methods of operations research : ZOR
Series Titel
Book Title
Publisher
Berlin ; Heidelberg : Springer
Link to publishers version
Abstract
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.
Description
Keywords
Citation
Berthold, H., Heitsch, H., Henrion, R., & Schwientek, J. (2021). On the algorithmic solution of optimization problems subject to probabilistic/robust (probust) constraints (Berlin ; Heidelberg : Springer). Berlin ; Heidelberg : Springer. https://doi.org//10.1007/s00186-021-00764-8
Collections
License
CC BY 4.0 Unported