40 citations · 166 across the 21 of their papers we have counts for
22 papers
Feature Selection for Data-driven Explainable Optimization
Kevin-Martin Aigner, Marc Goerigk, Michael Hartisch +3
Mathematical optimization, although often leading to NP-hard models, is now capable of solving even large-scale instances within reasonable time. However, the primary focus is ofte…
Scenario Reduction for Distributionally Robust Optimization
Kevin-Martin Aigner, Sebastian Denzler, Frauke Liers +2
Stochastic and (distributionally) robust optimization problems often become computationally challenging as the number of scenarios or data points increases. Scenario reduction is t…
Optimized Noise Suppression for Quantum Circuits
Friedrich Wagner, Daniel J. Egger, Frauke Liers
Quantum computation promises to advance a wide range of computational tasks. However, current quantum hardware suffers from noise and is too small for error correction. Thus, accur…
Quality Control in Particle Precipitation via Robust Optimization
Martina Kuchlbauer, Jana Dienstbier, Adeel Muneer +4
In this work, we propose a robust optimization approach to mitigate the impact of uncertainties in particle precipitation. Our model incorporates partial differential equations, mo…
A Framework for Data-Driven Explainability in Mathematical Optimization
Kevin-Martin Aigner, Marc Goerigk, Michael Hartisch +2
Advancements in mathematical programming have made it possible to efficiently tackle large-scale real-world problems that were deemed intractable just a few decades ago. However, p…
A Digital Twin to overcome long-time challenges in Photovoltaics
Larry Lüer, Marius Peters, Ana Sunčana Smith +9
The recent successes of emerging photovoltaics (PV) such as organic and perovskite solar cells are largely driven by innovations in material science. However, closing the gap to co…