Publications

Robust and Bilevel Optimization

A K-adaptability Approach to Proton Radiation Therapy Robust Treatment Planning.

Qiu, Z., Ajdari, A., Bobić, M., Bortfeld, T., Hertog, D. D., Kurtz, J., & Lee, H | arXiv preprint arXiv:2508.07368. | 2025

Data-driven prediction of relevant scenarios for robust combinatorial optimization.

Goerigk, M., & Kurtz, J. | Computers & Operations Research, 174, 106886 | 2025

Connections between Robust and Bilevel Optimization.

Goerigk, M., Kurtz, J., Schmidt, M., & Thürauf, J. | Open Journal of Mathematical Optimization, 6, 1-17 | 2025

Approximation Guarantees for Min-Max-Min Robust Optimization and-Adaptability Under Objective Uncertainty.

Kurtz, J. | SIAM Journal on Optimization, 34(2), 2121-2149 | 2024

Neur2BiLO: Neural Bilevel Optimization.

Dumouchelle, J., Julien, E., Kurtz, J., & Khalil, E. B. | In Proceedings of the 38th International Conference on Neural Information Processing Systems (pp. 86688-86719). | 2024

A Frank-Wolfe Algorithm for Oracle-based Robust Optimization.

Besançon, M., & Kurtz, J. | arXiv preprint arXiv:2411.19848 | 2024

Bounding the Optimal Number of Policies for Robust K-Adaptability.

Kurtz, J. | arXiv preprint arXiv:2409.12630 | 2024

Neur2RO: Neural two-stage robust optimization.

Dumouchelle, J., Julien, E., Kurtz, J., & Khalil, E. B. | The Twelfth International Conference on Learning Representations | 2024

Deep Learning for Two-Stage Robust Integer Optimization.

Dumouchelle, J., Julien, E., Kurtz, J., & Khalil, E. B. | arXiv preprint arXiv:2310.04345 | 2023

Data-driven robust optimization using deep neural networks.

Goerigk, M., & Kurtz, J. | Computers & Operations Research, 151, 106087 | 2023

Oracle-based algorithms for binary two-stage robust optimization.

Kämmerling, N., & Kurtz, J. | Computational Optimization and Applications, 77(2), 539-569 | 2020

Min–max–min robustness for combinatorial problems with discrete budgeted uncertainty.

Goerigk, M., Kurtz, J., & Poss, M. | Discrete Applied Mathematics, 285, 707-725 | 2020

A robust approach to the capacitated vehicle routing problem with uncertain costs.

Eufinger, L., Kurtz, J., Buchheim, C., & Clausen, U. | INFORMS Journal on Optimization, 2(2), 79-95 | 2020

Faster algorithms for min-max-min robustness for combinatorial problems with budgeted uncertainty.

Chassein, A., Goerigk, M., Kurtz, J., & Poss, M. | European Journal of Operational Research, 279(2), 308-319 | 2019

Robust combinatorial optimization under budgeted–ellipsoidal uncertainty.

Kurtz, J. | EURO Journal on Computational Optimization, 6(4), 315-337 | 2018

Robust combinatorial optimization under convex and discrete cost uncertainty.

Buchheim, C., & Kurtz, J. | EURO Journal on Computational Optimization, 6(3), 211-238 | 2018

Complexity of min–max–min robustness for combinatorial optimization under discrete uncertainty.

Buchheim, C., & Kurtz, J. | Discrete Optimization, 28, 1-15 | 2018

Min–max–min robust combinatorial optimization.

Buchheim, C., & Kurtz, J. | Mathematical Programming, 163(1), 1-23 | 2017

Min-max-min robustness: a new approach to combinatorial optimization under uncertainty based on multiple solutions.

Buchheim, C., & Kurtz, J. | Electronic Notes in Discrete Mathematics, 52, 45-52 | 2016

Explainable Optimization and XAI

Counterfactual explanations for linear optimization.

Kurtz, J., Birbil, Ş. İ., & den Hertog, D. | European Journal of Operational Research | 2025

Coherent Local Explanations for Mathematical Optimization.

Otto, D., Kurtz, J., & Birbil, S. I. | arXiv preprint arXiv:2502.04840 | 2025

Explainable Decision Making: How to explain optimization models in Operations Research.

Kurtz, J. | STAtOR March 2025 | 2025

Finding regions of counterfactual explanations via robust optimization.

Maragno, D., Kurtz, J., Röber, T. E., Goedhart, R., Birbil, Ş. I., & den Hertog, D. | INFORMS Journal on Computing, 36(5), 1316-1334 | 2024

Publications

Robust and Bilevel Optimization

A K-adaptability Approach to Proton Radiation Therapy Robust Treatment Planning.

Data-driven prediction of relevant scenarios for robust combinatorial optimization.

Connections between Robust and Bilevel Optimization.

Approximation Guarantees for Min-Max-Min Robust Optimization and-Adaptability Under Objective Uncertainty.

Neur2BiLO: Neural Bilevel Optimization.

A Frank-Wolfe Algorithm for Oracle-based Robust Optimization.

Bounding the Optimal Number of Policies for Robust K-Adaptability.

Neur2RO: Neural two-stage robust optimization.

Deep Learning for Two-Stage Robust Integer Optimization.

Data-driven robust optimization using deep neural networks.

Oracle-based algorithms for binary two-stage robust optimization.

Min–max–min robustness for combinatorial problems with discrete budgeted uncertainty.

A robust approach to the capacitated vehicle routing problem with uncertain costs.

Faster algorithms for min-max-min robustness for combinatorial problems with budgeted uncertainty.

Robust combinatorial optimization under budgeted–ellipsoidal uncertainty.

Robust combinatorial optimization under convex and discrete cost uncertainty.

Complexity of min–max–min robustness for combinatorial optimization under discrete uncertainty.

Min–max–min robust combinatorial optimization.

Min-max-min robustness: a new approach to combinatorial optimization under uncertainty based on multiple solutions.

Explainable Optimization and XAI

Counterfactual explanations for linear optimization.

Coherent Local Explanations for Mathematical Optimization.

Explainable Decision Making: How to explain optimization models in Operations Research.

Finding regions of counterfactual explanations via robust optimization.

Machine Learning and Deep Learning

Enhancing Decision Making Through the Integration of Large Language Models and Operations Research Optimization.

Ensemble Methods for Robust Support Vector Machines using Integer Programming.

Efficient and robust mixed-integer optimization methods for training binarized deep neural networks.

An Integer Programming Approach to Deep Neural Networks with Binary Activation Functions.

Other Topics

Discrete optimization methods for group model selection in compressed sensing.

Radial eigenfunctions for the game-theoretic p-Laplacian on a ball.

Popular Articles

Explainable Decision Making: How to explain optimization models in Operations Research.