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math.OC2026
Decision-Tree Surrogates for Weak Counterfactual Explanations in Integer Optimization
Marc Goerigk, Jannis Kurtz, Sebastian Merten
The concept of counterfactual explanations (CEs) has recently gained increasing attention for deriving explanations of mathematical optimization problems. For a given problem, a co…
math.OC2026
Sparse Linear Surrogates for Interpretable Budget Allocation
Marc Goerigk, Michael Hartisch, Sebastian Merten
To address the demand for inherently interpretable optimization methods, we introduce novel linear surrogates for budget allocation problems. These surrogates consist of sparse lin…
math.OC2024
Feature-Based Interpretable Surrogates for Optimization
Marc Goerigk, Michael Hartisch, Sebastian Merten +1
For optimization models to be used in practice, it is crucial that users trust the results. A key factor in this aspect is the interpretability of the solution process. A previous…