This page is dedicated to making my research material as accessible as possible, in particular, I try to provide the following:
- Method. Access to the transformation of raw data into aggregated forms, such as averages, ECDFs and more.
- Code. Access to the implementation code for the paper, allowing other researchers to replicate and build upon our work.
- Data. Access to the datasets used in our numerical experiments, promoting reproducibility and collaborative research.
- Access. Links to open-access published articles or online preprints.
- Resources. Access to supplementary materials designed to extend the outreach and understanding of my research; e.g., slides.
| Code | Year | Title | Authors | Method | Code | Data | Access | Resources | Status |
|---|---|---|---|---|---|---|---|---|---|
| AE | 2023 | Using Column Generation in Column-and-Constraint Generation for Adjustable Robust Optimization | Lefebvre, H., Schmidt, M., Thürauf, J. | Preprint | |||||
| AD | 2022 | An Exact Approach for Convex Adjustable Robust Optimization | Lefebvre, H., Malaguti, E., Monaci, M. | Preprint | |||||
| AC | 2022 | Adjustable Robust Optimization with Discrete Uncertainty | Lefebvre, H., Malaguti, E., Monaci, M. | Article | |||||
| AB | 2022 | Adjustable Robust Optimization with Objective Uncertainty | Lefebvre, H., Detienne, B., Malaguti, E., Monaci, M. | Article | |||||
| AA | 2022 | A Two-Stage Robust Approach for the Weighted Number of Tardy Jobs with Objective Uncertainty | Clautiaux, F., Detienne, B., Lefebvre, H. | Article |