As scientists, we should aim for the highest standards of transparency and accessibility.
As much as I can, I make available all the material related to my papers. In particular:
- Method. How is data transformed to reach the conclusions which are claimed in my contributions.
- Code. How was everything implemented (when relevant) so that one can reproduce it.
- Data. What data was used to perform the experiments (when relevant).
- Access. Where can an open-access or preprint be found online.
- Resources. Any additional resource making it easier to understand/criticize the work done.
Legend: Available · Not Applicable · Not Available.
| ID |
Year |
Title |
Authors |
Method |
Code |
Data |
Access |
Resources |
Status |
| AH |
2024 |
Computing Counterfactual Explanations for Linear Optimization: A New Class of Bilevel Models and a Tailored Penalty Alternating Direction Method |
Lefebvre, H., Schmidt, M. |
|
|
|
|
|
Preprint |
| AG |
2024 |
Exact Augmented Lagrangian Duality for Nonconvex Mixed-Integer Nonlinear Optimization |
Lefebvre, H., Schmidt, M. |
|
|
|
|
|
Preprint |
| AF |
2024 |
On Coupling Constraints in Linear Bilevel Optimization |
Henke, D., Lefebvre, H., Schmidt, M., Thürauf, J. |
|
|
|
|
|
Accepted |
| AE |
2023 |
Using Column Generation in Column-and-Constraint Generation for Adjustable Robust Optimization |
Lefebvre, H., Schmidt, M., Thürauf, J. |
|
|
|
|
|
Preprint |
| AD |
2022 |
Exact Approaches 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. |
|
|
|
|
|
Published |
| AB |
2022 |
Adjustable Robust Optimization with Objective Uncertainty |
Lefebvre, H., Detienne, B., Malaguti, E., Monaci, M. |
|
|
|
|
|
Published |
| AA |
2022 |
A Two-stage Robust Approach for Minimizing the Weighted Number of Tardy Jobs with Objective Uncertainty |
Clautiaux, F., Detienne, B., Lefebvre, H. |
|
|
|
|
|
Published |