Lea Strubberg

 

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

Projects

• Combinatorial Network Flow Methods for Instationary Gas Flows and Gas Market Problems
  SFB Transregio TRR154 Deutsche Forschungsgemeinschaft (DFG). Project heads: Max Klimm, Marc Pfetsch and Martin Skutella
• Tropical Mechanism Design
  Math+ project AA3-5. Project heads: Michael Joswig and Max Klimm

Publications

to appear

• Incremental–Decremental Maximization (Yann Disser, Max Klimm, Annette Lutz, and Lea Strubberg)
  Acta Informatica, to appear.
  Preliminary version (WAOA 2025) Bibtex Abstract
  @article{DisserKlimmLutz+2026,
  author = {Yann Disser and Max Klimm and Annette Lutz and Lea Strubberg},
  title = {Incremental–Decremental Maximization},
  journal = {Acta Informatica},
  year = {to appear},
  }
  
  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 algorithm and a more sophisticated deterministic algorithm, both of which find an order in which to transform the elements while maintaining a large utility during all stages of transformation, relative to an optimal 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 functions satisfying the gross substitutes property. Our results show that incremental–decremental max imization is substantially more difficult than incremental max imization.
• Gas2Hydro – A Combined Natural Gas–Hydrogen Instance (Daniela Bernhard, Julian Born, Yann Disser, Caroline Geiersbach, Johannes Hahn, Anton Hoof, and Lea Strubberg)
  Chapter in Mathematical Modelling, Simulation and Optimization using the Example of Gas Networks, to appear.
  Bibtex Abstract
  @incollection{BernhardBornDisser+2026,
  author = {Daniela Bernhard and Julian Born and Yann Disser and Caroline Geiersbach and Johannes Hahn and Anton Hoof and Lea Strubberg},
  title = {Gas2Hydro -- A Combined Natural Gas--Hydrogen Instance},
  booktitle = {Mathematical Modelling, Simulation and Optimization using the Example of Gas Networks},
  year = {to appear},
  noseries = {},
  novolume = {},
  noeditor = {Alexander Martin and Falk Hante and Jens Lang and Frauke Liers and Marc Pfetsch and Caren Tischendorf and Stefan Ulbrich},
  }
  
  We introduce Gas2Hydro, a publicly available instance designed to model, optimize, and test the transition from natural gas to hydrogen networks. While natural gas and hydrogen share similar transport principles, their physical properties differ, and until now, no open dataset exists to study their combined operation. Based on the development plans of the German gas transmission operators (FNB Gas), we construct a realistic network that reflects both the current natural gas infrastructure and the planned hydrogen core network. The instance is implemented in a format compatible with the established GasLib library to ensure seamless integration with existing gas network optimization tools. In addition, we provide demand and supply scenarios derived from official planning frameworks and survey data. Although simplified in some aspects, Gas2Hydro represents the first openly accessible benchmark instance to support methodological research and planning studies for the transition towards a hydrogen economy.

2026

• Approximating the Network Design Problem for Potential-Based Flows (Max Klimm, Marc Pfetsch, Martin Skutella, and Lea Strubberg)
  WAOA 2026 – Proc. 24th Workshop on Approximation and Online Algorithms.
  Bibtex Abstract
  @inproceedings{KlimmPfetschSkutella+2026,
  author = {Max Klimm and Marc Pfetsch and Martin Skutella and Lea Strubberg},
  title = {Approximating the Network Design Problem for Potential-Based Flows},
  booktitle = {WAOA 2026 – Proc. 24th Workshop on Approximation and Online Algorithms},
  year = {2026},
  }
  
  We develop efficient algorithms for a fundamental network design problem arising in potential-based flow models, which are central to many energy transport networks (e.g., hydrogen and electricity). In contrast to classical network flow problems, the nonlinearities inherent in potential-based networks introduce significant new challenges. We address these challenges through intricate reductions to classical combinatorial optimization problems, such as (constrained) shortest path problems, enabling the application of well-established algorithmic techniques to compute exact and approximate solutions efficiently. Finally, we complement these algorithmic results with matching complexity results concerning the hardness and non-approximability of the considered problem variants.

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.
  doi Bibtex Abstract
  @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.
  doi Full version (Acta Inf 2026) Bibtex Abstract
  @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.

Recent Talks

• Approximating the Network Design Problem for Potential-Based Flows, SIAM Conference on Optimization (OP26), 05. Jun 26
• Valid Cuts for the Design of Potential-based Flow Networks, IPCO 2025, 11. Jun 25
• Recovering potential-based flow networks during operations and under uncertainty, Santiago Summer Workshop on Combinatorial Optimization 2025, 21. Jan 25
• Recovering potential-based flow networks during operations and under uncertainty, Klagenfurt-Berlin Workshop on Multiple Perspectives in Optimization, 06. Jun 24
• To couple models for cardiac electrophysiology with transparent interface conditions, International Conference on Operations Research, 30. Aug 23