Lea Strubberg
PhD student
Fakultät II - Mathematik und Naturwissenschaften
Institut für Mathematik, MA 5-2
Technische Universität Berlin
Straße des 17. Juni 136
10623 Berlin
Office: MA 664
Telephone: +49 30 314 25739
Email: (lastname)@math.tu-berlin.de
Publications
2025
- Valid Cuts for the Design of Potential-based Flow Networks (Pascal Börner, Max Klimm, Annette Lutz, Marc Pfetsch, Martin Skutella, and Lea Strubberg)
IPCO 2025 – Proc. 26th Conference on Integer Programming and Combinatorial Optimization, pp. 142–156.
@inproceedings{BoernerKlimmLutz+2025,
author = {Pascal Börner and Max Klimm and Annette Lutz and Marc Pfetsch and Martin Skutella and Lea Strubberg},
title = {Valid Cuts for the Design of Potential-based Flow Networks},
booktitle = {IPCO 2025 – Proc. 26th Conference on Integer Programming and Combinatorial Optimization},
pages = {142--156},
doi = {10.1007/978-3-031-93112-3_11},
year = {2025},
}
The construction of a cost minimal network for flows obeying physical laws is an important problem for the design of electricity, water, hydrogen, and natural gas infrastructures. We formulate this problem as a mixed-integer non-linear program. Its non-convexity, due to the potential flow, together with the binary variables, indicating the decision to build a connection, make these problems challenging to solve. We develop a novel class of valid inequalities on the fractional relaxations of the binary variables. Further, we show that this class of inequalities can be separated in polynomial for solutions to a fractional relaxation. This makes it possible to incorporate these inequalities into a branch-and-bound algorithm. The advantage of these inequalities is lastly demonstrated in a computational study on the design of real-world gas transport networks.
- Incremental–Decremental Maximization (Yann Disser, Max Klimm, Annette Lutz, and Lea Strubberg)
WAOA 2025 – Proc. 23th Workshop on Approximation and Online Algorithms, pp. 97–110.
@inproceedings{DisserKlimmLutz+2025,
author = {Yann Disser and Max Klimm and Annette Lutz and Lea Strubberg},
title = {Incremental–Decremental Maximization},
booktitle = {WAOA 2025 – Proc. 23th Workshop on Approximation and Online Algorithms},
year = {2025},
doi = {10.1007/978-3-032-06706-7_7},
pages = {97--110},
}
We introduce a framework for incremental–decremental maximization that captures the gradual transformation or renewal of infrastructures. In our model, an initial solution is transformed one element at a time and the utility of an intermediate solution is given by the sum of the utilities of the transformed and untransformed parts. We propose a simple randomized and a deterministic algorithm that both find an order in which to transform the elements while maintaining a large utility during all stages of transformation, relative to an optimum solution for the current stage. More specifically, our algorithms yield competitive solutions for utility functions of bounded curvature and/or generic submodularity ratio, and, in particular, for submodular functions, and gross substitute functions. Our results exhibit that incremental–decremental maximization is substantially more difficult than incremental maximization.
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