Deborah Hendrych
I am interested in Mixed-Integer Non-Linear Optimization and first-order methods for solving non-linear, convex optimization problems. Currently, I am working on a Branch-and-Bound framework using Frank-Wolfe to solve the node problems.
📬 Contact
- office
- Room 3106 at ZIB
- hendrych (at) zib.de
- languages
- German and English
🎓 Curriculum vitae
- since 2023
- Researcher at ZIB
- 2021 to spring 2023
- Research Assistant at ZIB
- autumn 2020 to spring 2021
- Tutor at BHT
- autumn 2016 to spring 2018
- Tutor at BHT
- 2023
- M.Sc. in Mathematics at FUB
- Apr 2019
- B.Sc. in Mathematics at BHT
📝 Publications and preprints
Preprints
- Hendrych, D., Troppens, H., Besançon, M., and Pokutta, S. (2022). Convex Integer Optimization with Frank-Wolfe Methods.
[arXiv]
[slides]
[code]
[BibTeX]
Conference proceedings
- Sharma, K., Hendrych, D., Besançon, M., and Pokutta, S. (2024). Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe. Proceedings of INFORMS Optimization Society Conference.
[arXiv]
[BibTeX]
- Hendrych, D., Besançon, M., and Pokutta, S. (2024). Solving the Optimal Experiment Design Problem with Mixed-integer Convex Methods. Proceedings of Symposium on Experimental Algorithms.
DOI: 10.4230/LIPIcs.SEA.2024.16
[arXiv]
[code]
[BibTeX]
🔬 Projects
Convex Solver Adaptivity for Mixed-integer Optimization
We will investigate mixed-integer optimization with convex objectives using error-adaptive convex solvers in branch-and-bound. Focusing on improving lower bounds and balancing computational costs, we aim to develop a faster branch-and-bound methodology by leveraging modern MILP techniques and error-adaptive methods. Key aspects include warm-starting and controlled inexactness in early termination.
MATH+ AA3-15
Apr 2023 to Mar 2026
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