3 papers
math.OC2025
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…
math.OC2025
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…
math.OC2023
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…