Mirko Hahn
PhD Student in the MathOpt research group
at the Faculty of Mathematics
Address
Universitätsplatz 2, 02-204
39106 Magdeburg, Germany
phone: +49 391 67-52207
Short CV
A long version is available on request.Education
06/2018
present
Otto von Guericke University Magdeburg
Ph.D. candidate and research assistant
10/2013
05/2016
Otto von Guericke University Magdeburg
Master of Science in Mathematics
10/2010
10/2013
Otto von Guericke University Magdeburg
Bachelor of Science in Mathematics
Experience
06/2016
06/2018
Argonne National Laboratory, Lemont, IL, USA
Predoctoral Appointee, Mathematics and Computer Science Division
01/2015
05/2015
Volkswagen Aktiengesellschaft, Wolfsburg, Germany
Internship: Traffic Modelling
Research interests
Mixed-integer Nonlinear Optimization
Optimization with ODE and PDE Constraints
Optimization with Set-Valued Variables
Applications in Gas and Power Networks
Applications in Topology Optimization
Publications
7 / 7
2023
article
Binary Optimal Control by Trust-Region Steepest Descent
Mathematical Programming
@article{Hahn2023,
author = {Hahn, Mirko and Leyffer, Sven and Sager, Sebastian},
title = {Binary Optimal Control by Trust-Region Steepest Descent},
journal = {Mathematical Programming},
year = {2023},
volume = {197},
number = {1},
pages = {147--190},
doi = {10.1007/s10107-021-01733-z}
}
2023
article
On convergence of binary trust-region steepest descent
Journal of Nonsmooth Analysis and Optimization
@article{Manns2023,
author = {Manns, Paul and Hahn, Mirko and Kirches, Christian and Leyffer, Sven and Sager, Sebastian},
title = {On convergence of binary trust-region steepest descent},
journal = {Journal of Nonsmooth Analysis and Optimization},
publisher = {Episciences. org},
year = {2023},
volume = {4},
pages = {10164},
doi = {10.46298/jnsao-2023-10164}
}
2022
incollection
Decomposition and approximation for PDE-constrained mixed-integer optimal control
SPP1962 Special Issue Non-Smooth and Complementarity-Based Distributed Parameter Systems
@incollection{Hahn2022a,
author = {Hahn, M. and Kirches, C. and Manns, P. and Sager, S. and Zeile, C.},
title = {Decomposition and approximation for PDE-constrained mixed-integer optimal control},
booktitle = {SPP1962 Special Issue Non-Smooth and Complementarity-Based Distributed Parameter Systems},
publisher = {Birkh\"{a}user},
year = {2022},
editor = {Hinterm\"{u}ller, M. et al.},
pages = {283--306},
url = {https://mathopt.de/publications/Hahn2019.pdf}
}
2022
article
Autonomous traffic at intersections: an optimization-based analysis of possible time, energy, and CO2 savings
Networks
@article{Le2022,
author = {Le, D.D. and Merkert, M. and Sorgatz, S. and Hahn, M. and Sager, S.},
title = {Autonomous traffic at intersections: an optimization-based analysis of possible time, energy, and {CO2} savings},
journal = {Networks},
year = {2022},
volume = {79},
number = {3},
pages = {338--363},
url = {https://optimization-online.org/?p=16226},
doi = {10.1002/net.22078}
}
2020
inproceedings
pycombina: An Open-Source Tool for Solving Combinatorial Approximation Problems arising in Mixed-Integer Optimal Control
IFAC
@inproceedings{Buerger2020,
author = {B\"urger, A. and Zeile, C. and Hahn, M. and Altmann-Dieses, A. and Sager, S. and Diehl, M.},
title = {pycombina: An Open-Source Tool for Solving Combinatorial Approximation Problems arising in Mixed-Integer Optimal Control},
journal = {IFAC},
year = {2020},
volume = {53},
pages = {6502--6508},
doi = {10.1016/j.ifacol.2020.12.1799}
}
2020
incollection
Power-to-Chemicals: A Superstructure Problem for Sustainable Syngas Production
Mathematical Modeling, Simulation and Optimization for Power Engineering and Management
@incollection{Garmatter2020,
author = {Garmatter, D. and Maggi, A. and Wenzel, M. and Monem, S. and Hahn, M. and Stoll, M. and Sager, S. and Benner, P. and Sundmacher, K.},
title = {Power-to-Chemicals: A Superstructure Problem for Sustainable Syngas Production},
booktitle = {Mathematical Modeling, Simulation and Optimization for Power Engineering and Management},
publisher = {Springer},
year = {2020},
pages = {145--168}
}
2020
article
Inversion of Convection-Diffusion Equation with Discrete Sources
Optimization and Engineering
We present a convection-diffusion inverse problem that aims to identify an unknown number of sources and their locations. We model the sources using a binary function, and we show that the inverse problem can be formulated as a large-scale mixed-integer nonlinear optimization problem. We show empirically that current state-of-the-art mixed-integer solvers cannot solve this problem and that applying simple rounding heuristics to solutions of the relaxed problem can fail to identify the correct number and location of the sources. We develop two new rounding heuristics that exploit the value and a physical interpretation of the continuous relaxation solution, and we apply a steepest-descent improvement heuristic to obtain satisfactory solutions to both two- and three-dimensional inverse problems. We also provide the code used in our numerical experiments in open-source format.
@article{Sharma2019,
author = {Sharma, M. and Hahn, M. and Leyffer, S. and Ruthotto, L. and van Bloemen Waanders, B.},
title = {Inversion of Convection-Diffusion Equation with Discrete Sources},
journal = {Optimization and Engineering},
year = {2020},
doi = {10.1007/s11081-020-09536-5}
}