AI for Discrete Optimization (IMEN891N, Fall 2025)

(♦: In-class presentation by students)

Part III: Data-driven optimization

Week 12-13: Optimization under uncertainty

• Theory in robust optimization (Bertsimas et al. 2011, Gorissen et al. 2015, Bertsimas & den Hertog 2022)
  • 2005 Robust and Adaptive Optimization: A Tractable Approach to Optimization Under Uncertainty (by Dimitris Bertsimas @ MIT) (link)
  • 2019 DTU Seminar: Adaptive Robust Optimization and its Applications to Power Systems (by Antonio J. Conejo @ Ohio State University) (link)
• ♦ Data-driven robust optimization (Bertsimas et al. 2018, Goerigk & Kurtz 2023, Ning & You 2018)
  • 2017 AIChE Webinar: Machine Learning and Robust Optimization (by Fengqi You @ Cornell University) (link)
  • 2024 Robust Optimization Webinar: Learning for Decision-Making under Uncertainty (by Bartolomeo Stellato @ Princeton University) (link)

Week 14: Decision-focused learning

• ♦ Decision-focused learning (Wilder et al. 2019, Mandi et al. 2024)
  • 2024 CPAIOR Keynote: Decision-Focused Learning: Foundations, State of Art, Benchmarking & Opportunities (by Tias Guns @ KU Leuven) (link)
• ♦ Predict-then-optimize (Elmachtoub & Grigas 2022, Mandi et al. 2020, Tang & Khalil 2024)
  • 2022 CPAIOR Master Class: Learning, Optimization, and Generalization in the Predict-then-Optimize Setting (by Tias Guns @ KU Leuven) (link)
  • 2023 ACP Summer School: Predict-then-Optimize (by Elias B. Khalil @ University of Toronto) (link)

Part III — Reading list

• Bertsimas, Dimitris, Brown, David B., Caramanis, Constantine (2011). Theory and Applications of Robust Optimization. SIAM Review, 53(3), 464–501. (link)
• Gorissen, Bram L., Yanıkoğlu, İhsan, den Hertog, Dick (2015). A Practical Guide to Robust Optimization. Omega, 53, 124–137. (link)
• Bertsimas, Dimitris, den Hertog, D. (2022). Robust and Adaptive Optimization. Dynamic Ideas LLC.
• Bertsimas, Dimitris, Gupta, Vishal, Kallus, Nathan (2018). Data-Driven Robust Optimization. Mathematical Programming, 167(2), 235–292. (link)
• Goerigk, Marc, Kurtz, Jannis (2023). Data-Driven Robust Optimization Using Deep Neural Networks. Computers & Operations Research, 151, 106087. (link)
• Ning, Chao, You, Fengqi (2018). Data-Driven Stochastic Robust Optimization: General Computational Framework and Algorithm Leveraging Machine Learning for Optimization under Uncertainty in the Big Data Era. Computers & Chemical Engineering, 111, 115–133. (link)
• Wilder, Bryan, Dilkina, Bistra, Tambe, Milind (2019). Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 1658–1665. (link)
• Mandi, Jayanta, Kotary, James, Berden, Senne, Mulamba, Maxime, Bucarey, Victor, Guns, Tias, Fioretto, Ferdinando (2024). Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities. Journal of Artificial Intelligence Research, 80, 1623–1701. (link)
• Elmachtoub, Adam N., Grigas, Paul (2022). Smart “Predict, Then Optimize”. Management Science, 68(1), 9–26. (link)
• Mandi, Jayanta, Demirović, Emir, Stuckey, Peter J., Guns, Tias (2020). Smart Predict-and-Optimize for Hard Combinatorial Optimization Problems. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 1603–1610. (link)
• Tang, Bo, Khalil, Elias B. (2024). PyEPO: A PyTorch-based End-to-End Predict-Then-Optimize Library for Linear and Integer Programming. Mathematical Programming Computation, 16(3), 297–335. (link)