Tuesday, 14:15 - 14:40 h, Room: MA 141


Milos Kopa
Robustness in stochastic programs with risk and probabilistic constraints

Coauthor: Jitka Dupacova


The paper presents robustness results for stochastic programs with risk, stochastic dominance and probabilistic constraints. Due to their frequently observed lack of convexity and/or smoothness, these programs are rather demanding both from the computational and robustness point of view. Under suitable conditions on the structure of the problem, we exploit the contamination technique to analyze the resistance of optimal value with respect to the alternative probability distribution.
We apply this approach to mean-risk models and portfolio efficiency testing with respect to stochastic dominance criteria.


Talk 3 of the invited session Tue.2.MA 141
"Stochastic optimization - Confidence sets, stability, robustness" [...]
Cluster 22
"Stochastic optimization" [...]


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