TY - JOUR A1 - Kotil, Ayse A1 - Pelofske, Elijah A1 - Riedmüller, Stephanie A1 - Egger, Daniel J. A1 - Eidenbenz, Stephan A1 - Koch, Thorsten A1 - Woerner, Stefan T1 - Quantum Approximate Multi-Objective Optimization JF - Nature Computational Science N2 - The goal of multi-objective optimization is to understand optimal trade-offs between competing objective functions by finding the Pareto front, i.e., the set of all Pareto optimal solutions, where no objective can be improved without degrading another one. Multi-objective optimization can be challenging classically, even if the corresponding single-objective optimization problems are efficiently solvable. Thus, multi-objective optimization represents a compelling problem class to analyze with quantum computers. In this work, we use low-depth Quantum Approximate Optimization Algorithm to approximate the optimal Pareto front of certain multi-objective weighted maximum cut problems. We demonstrate its performance on an IBM Quantum computer, as well as with Matrix Product State numerical simulation, and show its potential to outperform classical approaches. Y1 - 2025 U6 - https://doi.org/10.1038/s43588-025-00873-y SP - 1168 EP - 1177 ER - TY - JOUR A1 - Zittel, Janina A1 - Petkovic, Milena A1 - Einck, Mathias T1 - Forecasting Hourly Gas Flows JF - Foresight - The International Journal of Applied Forecasting Y1 - 2025 UR - https://econpapers.repec.org/RePEc:for:ijafaa:y:2025:i:79:p:40-44 VL - 79 SP - 40 EP - 44 ER - TY - JOUR A1 - Shimada, Naoki A1 - Mako, Sato A1 - Yaegashi, Yuta A1 - Koch, Thorsten A1 - Le, Thi Thai T1 - An Application of Modified S-CLSVOF Method to Kelvin-Helmholtz Instability and Comparison with Theoretical Result JF - Journal of Chemical Engineering of Japan N2 - This study focuses on validating a two-phase flow solver based on the modified Simple Coupled Level Set and Volume of Fluid method (Uchihashi et al. (2023)) through viscous Kelvin-Helmholtz instability simulations. Our numerical simulation results are compared with the ones given by Funada and Joseph (2001) to provide reliable predictions of interface behavior under the influence of viscosity. The primary goal is to accurately assess the solver's ability to replicate theoretical analysis of interface behaviors under various conditions. First, the wave between two fluids of identical density is calculated. In addition, the effect of surface tension is investigated. By comparing growth rates, numerical simulations obtain well-agreements with the analytical results on the effect of the fluid viscosity, the wave number, and the surface tension. Finally, fluid density is changed to an air-water system. When relative velocity U is smaller than the criteria of relative velocity U_c given by analytical solutions, the wave is not broken. However, waves are splashed into droplets in the condition of U>U_c. This result agrees with the analysis by Funada and Joseph (2001). These findings provide a robust framework for applying the solver to more complex two-phase flow problems, supporting advancements in numerical simulations of fluid interfaces. Y1 - 2025 U6 - https://doi.org/10.1080/00219592.2025.2451953 VL - 58 IS - 1 PB - Taylor and Francis ER - TY - JOUR A1 - Rong, Guoyang A1 - Chen, Ying A1 - Koch, Thorsten A1 - Honda, Keisuke T1 - Assessing data quality in citation analysis: A case study of web of science and Crossref JF - Journal of Informetrics Y1 - 2026 U6 - https://doi.org/10.1016/j.joi.2026.101775 SN - 1751-1577 VL - 20 IS - 1 PB - Elsevier BV ER - TY - GEN A1 - Kempke, Nils-Christian A1 - Koch, Thorsten T1 - Low-precision first-order method-based fix-and-propagate heuristics for large-scale mixed-integer linear optimization N2 - We investigate the use of low-precision first-order methods (FOMs) within a fix-and-propagate (FP) framework for solving mixed-integer programming problems (MIPs). FOMs, using only matrix-vector products instead of matrix factorizations, are well suited for GPU acceleration and have recently gained more attention for their application to large-scale linear programming problems (LPs). We employ PDLP, a variant of the Primal-Dual Hybrid Gradient (PDHG) method specialized to LP problems, to solve the LP-relaxation of our MIPs to low accuracy. This solution is used to motivate fixings within our fix-and-propagate framework. We implemented four different FP variants using primal and dual LP solution information. We evaluate the performance of our heuristics on MIPLIB 2017, showcasing that the low-accuracy LP solution produced by the FOM does not lead to a loss in quality of the FP heuristic solutions when compared to a high-accuracy interior-point method LP solution. Further, we use our FP framework to produce high-accuracy solutions for large-scale (up to 243 million non-zeros and 8 million decision variables) unit-commitment energy-system optimization models created with the modeling framework REMix. For the largest problems, we can generate solutions with under 2% primal-dual gap in less than 4 hours, whereas commercial solvers cannot generate feasible solutions within two days of runtime. This study represents the first successful application of FOMs in large-scale mixed-integer optimization, demonstrating their efficacy and establishing a foundation for future research in this domain. T3 - ZIB-Report - 25-04 KW - Integer programming KW - Large scale optimization KW - Linear Programming KW - Primal heuristics KW - OR in energy Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-99612 SN - 1438-0064 ER - TY - CHAP A1 - Ghannam, Mohammed A1 - Gleixner, Ambros T1 - Hybrid Genetic Search for Dynamic Vehicle Routing with Time Windows T2 - Operations Research Proceedings 2023. OR 2023 Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-58405-3_35 ER - TY - CHAP A1 - Pedersen, Jaap A1 - Lindner, Niels A1 - Rehfeldt, Daniel A1 - Koch, Thorsten T1 - Comparing Branching Rules for the Quota Steiner Tree Problem with Interference T2 - Operations Research Proceedings 2025 N2 - Branching decisions play a crucial role in branch-and-bound algorithms for solving combinatorial optimization problems. In this paper, we investigate several branching rules applied to the Quota Steiner Tree Problem with Interference (QSTPI). The Quota Steiner Tree Problem (QSTP) generalizes the classical Steiner Tree Problem (STP) in graphs by seeking a minimum-cost tree that connects a subset of profit-associated vertices whose cumulative profit meets or exceeds a given quota. The QSTPI introduces interference among vertices: Selecting certain vertices simultaneously reduces their individual contributions to the overall profit. This problem arises, for example, in positioning and connecting wind turbines, where turbines possibly shadow other turbines, reducing their energy yield. Unlike classical STP variants, large QSTPI instances require significantly more branching to compute provably optimal solutions. In contrast to branching on variables, we utilize the combinatorial structure of the QSTPI by branching on the graph's vertices. We adapt classical and problem-specific branching rules and present a comprehensive computational study comparing the effectiveness of these branching strategies. Y1 - 2026 ER - TY - CHAP A1 - Koch, Thorsten A1 - Kempke, Nils-Christian A1 - Lindner, Niels A1 - Mehl, Lukas A1 - Wetzel, Manuel A1 - Zittel, Janina T1 - High-Performance Robust Energy System Planning with Storage: A Single-LP Approach T2 - Proceedings of URBSENSE 2026 - 1st International Workshop on URBan SENSEmaking and Intelligence for Safer Cities Y1 - 2026 ER - TY - JOUR A1 - Turner, Mark A1 - Berthold, Timo A1 - Besançon, Mathieu A1 - Koch, Thorsten T1 - Branching via Cutting Plane Selection: Improving Hybrid Branching N2 - Cutting planes and branching are two of the most important algorithms for solving mixed-integer linear programs. For both algorithms, disjunctions play an important role, being used both as branching candidates and as the foundation for some cutting planes. We relate branching decisions and cutting planes to each other through the underlying disjunctions that they are based on, with a focus on Gomory mixed-integer cuts and their corresponding split disjunctions. We show that selecting branching decisions based on quality measures of Gomory mixed-integer cuts leads to relatively small branch-and-bound trees, and that the result improves when using cuts that more accurately represent the branching decisions. Finally, we show how the history of previously computed Gomory mixed-integer cuts can be used to improve the performance of the state-of-the-art hybrid branching rule of SCIP. Our results show a $4\%$ decrease in solve time, and an $8\%$ decrease in number of nodes over affected instances of MIPLIB 2017. Y1 - 2023 PB - Springer ER - TY - JOUR A1 - Hadjidimitriou, Natalia Selini A1 - Koch, Thorsten A1 - Lippi, Marco A1 - Petkovic, Milena A1 - Mamei, Marco T1 - Spatial analysis of COVID-19 and the Russia–Ukraine war impacts on natural gas flows using statistical and machine learning models JF - World Wide Web Y1 - 2026 U6 - https://doi.org/https://doi.org/10.1007/s11280-025-01402-7 SN - 1386-145X VL - 29 IS - 2 PB - Springer Science and Business Media LLC ER - TY - GEN A1 - Kempke, Nils-Christian A1 - Maher, Stephen John A1 - Rehfeldt, Daniel A1 - Gleixner, Ambros A1 - Koch, Thorsten A1 - Uslu, Svenja T1 - Distributed Parallel Structure-Aware Presolving for Arrowhead Linear Programs N2 - We present a structure-aware parallel presolve framework specialized to arrowhead linear programs (AHLPs) and designed for high-performance computing (HPC) environments, integrated into the parallel interior point solver PIPS-IPM++. Large-scale LPs arising from automated model generation frequently contain redundancies and numerical pathologies that necessitate effective presolve, yet existing presolve techniques are primarily serial or structure-agnostic and can become time-consuming in parallel solution workflows. Within PIPS-IPM++, AHLPs are stored in distributed memory, and our presolve builds on this to apply a highly parallel, distributed presolve across compute nodes while keeping communication overhead low and preserving the underlying arrowhead structure. We demonstrate the scalability and effectiveness of our approach on a diverse set of AHLPs and compare it against state-of-the-art presolve implementations, including PaPILO and the presolve implemented within Gurobi. Even on a single machine, our presolve significantly outperforms PaPILO by a factor of 18 and Gurobi’s presolve by a factor of 6 in terms of shifted geometric mean runtime, while reducing the problems by a similar amount to PaPILO. Using a distributed compute environment, we outperform Gurobi's presolve by a factor of 13. T3 - ZIB-Report - 26-01 KW - Linear Programming KW - Presolving KW - Large-Scale Optimization KW - Distributed Parallel Computing KW - Arrowhead Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-103034 SN - 1438-0064 ER - TY - JOUR A1 - Sato, Mako A1 - Koch, Thorsten A1 - Le, Thi Thai T1 - Influence of frictional drag on Kelvin-Helmholtz instability in viscous fluids JF - Physics of Fluids N2 - The Kelvin-Helmholtz instability arises at the interface between two fluid layers with a tangential velocity discontinuity, significantly impacting the safety of systems in industrial applications. Despite extensive studies, many theoretical analyses neglect viscosity and frictional drag due to the complexity of solving the dispersion equation. However, including these effects is crucial, as viscosity alters the growth rate of the instability, while frictional drag influences energy dissipation and momentum transfer. In this study, these effects are incorporated into both finite and infinite flows. The assumption of a potential flow combined with a dissipation method is employed to derive the dispersion equation, providing a more tractable approach than direct calculation methods. The results indicate that, in the case of infinite flows, the frictional drag suppresses the growth of the instability for long waves (small wavenumber k) but enhances it for short waves (large k). In contrast, the surface tension dominates, while the frictional drag only slightly affects the growth rate in the case of finite flows bounded by solid walls. Y1 - 2026 U6 - https://doi.org/10.1063/5.0306177 VL - 38 IS - 1 PB - AIP Publishing CY - Physics of Fluids ER - TY - CHAP A1 - Riedmüller, Stephanie A1 - Zittel, Janina A1 - Koch, Thorsten T1 - Warm-starting Strategies in Scalarization Methods for Multi-Objective Optimization T2 - Operations Research Proceedings 2025 N2 - We explore how warm-starting strategies can be integrated into scalarization-based approaches for multi-objective optimization in (mixed) integer linear programming. Scalarization methods remain widely used classical techniques to compute Pareto-optimal solutions in applied settings. They are favored due to their algorithmic simplicity and broad applicability across continuous and integer programs with an arbitrary number of objectives. While warm-starting has been applied in this context before, a systematic methodology and analysis remain lacking. We address this gap by providing a theoretical characterization of warm-starting within scalarization methods, focusing on the sequencing of subproblems. However, optimizing the order of subproblems to maximize warm-start efficiency may conflict with alternative criteria, such as early identification of infeasible regions. We quantify these trade-offs through an extensive computational study. Y1 - 2026 ER -