collaborators

8 papers

math.OC2026

Robust Unit Commitment in District Heating Networks: Chance-Constrained and CVaR Optimization Under Demand Uncertainty

Annika Buchholz, Janina Zittel, Thorsten Koch

While district heating networks are a key component of the energy transition, their operational planning is challenging due to substantial uncertainty in heat demand. We address th…

math.OC2026

Benchmarking Realistic Synthetic Instances Against a Large-Scale District Heating Network: A Multi-Objective Optimization Study for Berlin

Annika Buchholz, Stephanie Riedmüller, Matthew Passage +1

Decarbonizing urban energy systems requires optimization approaches capable of handling the operational complexity of large-scale district heating networks. However, existing studi…

cs.DL2026

Reconnecting Fragmented Citation Networks with Semantic Augmentation

Vu Thi Huong, Annika Buchholz, Imene Khebouri +5

Citation graphs are fundamental tools for modeling scientific structure, but are often fragmented due to missing citations of scientifically connected articles. To address this iss…

math.OC2026

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers

Janina Zittel, Annika Buchholz, Michael Bussieck +5

Energy system optimization models are increasing in scope and resolution, yielding large and challenging linear programs. For a long time, the standard way to address such problems…

math.OC2025

Long-Term Multi-Objective Optimization for Integrated Unit Commitment and Investment Planning for District Heating Networks

Stephanie Riedmüller, Fabian Rivetta, Janina Zittel

The need to decarbonize the energy system has intensified the focus on district heating networks in urban and suburban areas. Therefore, exploring transformation pathways with reas…

math.OC2025

Warm-starting Strategies in Scalarization Methods for Multi-Objective Optimization

Stephanie Riedmüller, Janina Zittel, Thorsten Koch

We explore how warm-starting strategies can be integrated into scalarization-based approaches for multi-objective optimization in (mixed) integer linear programming. Scalarization…