5 citations · 5 across the 7 of their papers we have counts for
8 papers
Existence of Solutions in Bi-level Stochastic Linear Programming with Integer Variables
Johanna Burtscheidt, Matthias Claus
The addition of lower level integrality constraints to a bi-level linear program is known to result in significantly weaker analytical properties. Most notably, the upper level goa…
A Pessimistic Bilevel Stochastic Problem for Elastic Shape Optimization
Johanna Burtscheidt, Matthias Claus, Sergio Conti +3
We consider pessimistic bilevel stochastic programs in which the follower maximizes over a fixed compact convex set a strictly convex quadratic function, whose Hessian depends on t…
Bilevel Optimization under Uncertainty
Johanna Burtscheidt, Matthias Claus
We consider bilevel linear problems, where the right-hand side of the lower level problems is stochastic. The leader has to decide in a here-and-now fashion, while the follower has…
Risk-Averse Models in Bilevel Stochastic Linear Programming
J. Burtscheidt, M. Claus, S. Dempe
We consider bilevel linear problems, where some parameters are stochastic, and the leader has to decide in a here-and-now fashion, while the follower has complete information. In t…
On Risk-Averse Stochastic Semidefinite Programs with Continuous Recourse
Matthias Claus, Rüdiger Schultz, Kai Spürkel +1
The vast majority of the literature on stochastic semidefinite programs (stochastic SDPs) with recourse is concerned with risk-neutral models. In this paper, we introduce mean-risk…
Strong Convexity for Risk-Averse Two-Stage Models with Fixed Complete Linear Recourse
Matthias Claus, Kai Spürkel
This paper generalizes results concerning strong convexity of two-stage mean-risk models with linear recourse to distortion risk measures. Introducing the concept of (restricted) p…