TY - GEN A1 - Shinano, Yuji A1 - Vigerske, Stefan T1 - Smoothie: Mixing the strongest MIP solvers to solve hard MIP instances on supercomputers - Phase I development N2 - Mixed-Integer Linear Programming (MIP) is applicable to such a wide range of real-world decision problems that the competition for the best code to solve such problems has lead to tremendous progress over the last decades. While current solvers can solve some of the problems that seemed completely out-of-reach just 10 years ago, there are always relevant MIP problems that currently cannot be solved. With the Smoothie solver we intend to solve extremely hard MIP problems by building on the many years that went into the development of several state-of-the-art MIP solvers and by utilizing some of the largest computing resources available. The high-level task parallelization framework UG (Ubiquity Generator) is used and extended by Smoothie to build a solver that uses large-scale parallelization to distribute the solution of a single MIP on a shared- or distributed-memory computing infrastructure, thereby employing several established MIP solvers simultaneously. For the first development phase, which is the topic of this report, both FICO Xpress and Gurobi are used in concurrent mode on a single machine, while information on incumbent solutions and explored branch-and-bound subtrees is exchanged. A dynamic restarting mechanism ensures that solver configurations are selected that promise most suitable for the MIP to be solved. We report on initial findings using this early version of Smoothie on unsolved problems from MIPLIB 2017. T3 - ZIB-Report - 25-18 KW - MIPLIB, MIP, UG, Parallelization Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-101906 SN - 1438-0064 ER - TY - GEN A1 - Vu, Thi Huong A1 - Koch, Thorsten T1 - Clustering scientific publications: lessons learned through experiments with a real citation network N2 - Clustering scientific publications helps uncover research structures within bibliographic databases. Graph-based methods such as spectral, Louvain, and Leiden clustering are commonly used due to their ability to model citation networks. However, their effectiveness can diminish when applied to real-world data. This study evaluates these clustering algorithms on a citation graph of about 700,000 articles and 4.6 million citations from the Web of Science. The results show that while scalable methods like Louvain and Leiden perform efficiently, their default settings often yield poor partitioning. Meaningful outcomes require careful parameter tuning, especially for large networks with uneven structures, including a dense core and loosely connected papers. These findings highlight practical lessons about the challenges of large-scale data, method selection and tuning based on specific structures of bibliometric clustering tasks. T3 - ZIB-Report - 25-05 KW - graph clustering KW - citation networks KW - Web of Science KW - bibliometric analysis KW - unsupervised learning Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-100418 ER - TY - JOUR A1 - Kießling, David A1 - Leyffer, Sven A1 - Vanaret, Charlie T1 - A Unified Funnel Restoration SQP Algorithm JF - Mathematical Programming B N2 - We consider nonlinearly constrained optimization problems and discuss a generic double-loop framework consisting of basic algorithmic ingredients that unifies a broad range of nonlinear optimization solvers. This framework has been implemented in the open-source solver Uno, a Swiss Army knife-like C++ optimization framework that unifies many nonlinearly constrained nonconvex optimization solvers. We illustrate the framework with a sequential quadratic programming (SQP) algorithm that maintains an acceptable upper bound on the constraint violation, called a funnel, that is monotonically decreased to control the feasibility of the iterates. Infeasible quadratic subproblems are handled by a feasibility restoration strategy. Globalization is controlled by a line search or a trust-region method. We prove global convergence of the trust-region funnel SQP method, building on known results from filter methods. We implement the algorithm in Uno, and we provide extensive test results for the trust-region line-search funnel SQP on small CUTEst instances. Y1 - 2025 U6 - https://doi.org/10.1007/s10107-025-02284-3 ER - TY - JOUR A1 - Kempke, Nils-Christian A1 - Rehfeldt, Daniel A1 - Koch, Thorsten T1 - A Massively Parallel Interior-Point-Method for Arrowhead Linear Programs JF - SIAM Journal on Scientific Computing Y1 - 2025 ER - TY - JOUR A1 - Rong, Guoyang A1 - Chen, Ying A1 - Ma, Feicheng A1 - Koch, Thorsten T1 - Exploring Interdisciplinary Research Trends through Critical Years for Interdisciplinary Citation JF - Journal of Informetrics Y1 - 2025 U6 - https://doi.org/10.1016/j.joi.2025.101726 VL - 19 IS - 4 ER - TY - GEN A1 - Pedersen, Jaap A1 - Lindner, Niels A1 - Rehfeldt, Daniel A1 - Koch, Thorsten T1 - Integrated Wind Farm Design: Optimizing Turbine Placement and Cable Routing with Wake Effects N2 - An accelerated deployment of renewable energy sources is crucial for a successful transformation of the current energy system, with wind energy playing a key role in this transition. This study addresses the integrated wind farm layout and cable routing problem, a challenging nonlinear optimization problem. We model this problem as an extended version of the Quota Steiner Tree Problem (QSTP), optimizing turbine placement and network connectivity simultaneously to meet specified expansion targets. Our proposed approach accounts for the wake effect - a region of reduced wind speed induced by each installed turbine - and enforces minimum spacing between turbines. We introduce an exact solution framework in terms of the novel Quota Steiner Tree Problem with interference (QSTPI). By leveraging an interference-based splitting strategy, we develop an advanced solver capable of tackling large-scale problem instances. The presented approach outperforms generic state-of-the-art mixed integer programming solvers on our dataset by up to two orders of magnitude. Moreover, we demonstrate that our integrated method significantly reduces the costs in contrast to a sequential approach. Thus, we provide a planning tool that enhances existing planning methodologies for supporting a faster and cost-efficient expansion of wind energy. T3 - ZIB-Report - 25-01 Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-99218 SN - 1438-0064 ER - TY - GEN A1 - Kempke, Nils-Christian A1 - Kunt, Tim A1 - Katamish, Bassel A1 - Vanaret, Charlie A1 - Sasanpour, Shima A1 - Clarner, Jan-Patrick A1 - Koch, Thorsten T1 - Developing heuristic solution techniques for large-scale unit commitment models N2 - Shifting towards renewable energy sources and reducing carbon emissions necessitate sophisticated energy system planning, optimization, and extension. Energy systems optimization models (ESOMs) often form the basis for political and operational decision-making. ESOMs are frequently formulated as linear (LPs) and mixed-integer linear (MIP) problems. MIPs allow continuous and discrete decision variables. Consequently, they are substantially more expressive than LPs but also more challenging to solve. The ever-growing size and complexity of ESOMs take a toll on the computational time of state-of-the-art commercial solvers. Indeed, for large-scale ESOMs, solving the LP relaxation -- the basis of modern MIP solution algorithms -- can be very costly. These time requirements can render ESOM MIPs impractical for real-world applications. This article considers a set of large-scale decarbonization-focused unit commitment models with expansion decisions based on the REMix framework (up to 83 million variables and 900,000 discrete decision variables). For these particular instances, the solution to the LP relaxation and the MIP optimum lie close. Based on this observation, we investigate the application of relaxation-enforced neighborhood search (RENS), machine learning guided rounding, and a fix-and-propagate (FP) heuristic as a standalone solution method. Our approach generated feasible solutions 20 to 100 times faster than GUROBI, achieving comparable solution quality with primal-dual gaps as low as 1% and up to 35%. This enabled us to solve numerous scenarios without lowering the quality of our models. For some instances that Gurobi could not solve within two days, our FP method provided feasible solutions in under one hour. T3 - ZIB-Report - 25-03 KW - Energy system optimization models KW - Unit commitment KW - Mixed-integer programming KW - Large-scale optimization KW - Primal heuristics Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-99555 SN - 1438-0064 ER - TY - JOUR A1 - Le, Thi Thai A1 - Petkovic, Milena T1 - Predicting Fluid Interface Instability in Energy Systems for Sustainable Energy Transition JF - Operations Research Proceedings 2023. OR 2023. N2 - Due to the coexistence of different gases in underground storage, this work explores the interface stability's impact on energy storage, specifically during the injection and withdrawal of gases such as hydrogen and natural gas. A new approach of combing simulation and time series analysis is used to accurately predict instability modes in energy systems. Our simulation is based on the 2D Euler equations, solved using a second-order finite volume method with a staggered grid. The solution is validated by comparing them to experimental data and analytical solutions, accurately predicting the instability's behavior. We use time series analysis and state-of-the-art regime-switching methods to identify critical features of the interface dynamics, providing crucial insights into system optimization and design. Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-58405-3_45 SP - 349 EP - 356 PB - Springer ER - TY - CHAP A1 - Lindner, Niels A1 - Bartoszuk, Karolina A1 - Debgupta, Srinwanti A1 - Gering, Marie-Claire A1 - Muschner, Christoph A1 - Zittel, Janina T1 - Warm-starting modeling to generate alternatives for energy transition paths in the Berlin-Brandenburg area T2 - Operations Research Proceedings 2024. OR 2024 N2 - Energy system optimization models are key to investigate energy transition paths towards a decarbonized future. Since this approach comes with intrinsic uncertainties, it is insufficient to compute a single optimal solution assuming perfect foresight to provide a profound basis for decision makers. The paradigm of modeling to generate alternatives enables to explore the near-optimal solution space to a certain extent. However, large-scale energy models require a non-negligible computation time to be solved. We propose to use warm start methods to accelerate the process of finding close-to-optimal alternatives. In an extensive case study for the energy transition of the Berlin-Brandenburg area, we make use of the sector-coupled linear programming oemof-B3 model to analyze a scenario for the year 2050 with a resolution of one hour and 100% reduction of greenhouse gas emissions. We demonstrate that we can actually achieve a significant computational speedup. Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-92575-7_35 SP - 248 EP - 253 ER - TY - CHAP A1 - Stompor, Tomasz A1 - Zittel, Janina A1 - Koch, Thorsten A1 - Rusch, Beate T1 - Fully Algorithmic Librarian: Large-Scale Citation Experiments T2 - 20th International Society of Scientometrics and Informetrics Conference 2025, June 23-27, 2025 | Yerevan, Armenia N2 - The Fully Algorithmic Librarian (FAN) project explores application scenarios for algorithmic-intelligence(AI)-supported methods in academic libraries as central institutions for research support. To this end, the study builds on two algorithmic approaches for analyzing large-scale citation networks. A comparison of Web of Science (WoS) and OpenAlex structures using the PageRank algorithm reveals key differences. Additionally, a multi-label clustering technique designed for large-scale citation networks accounts for disciplinary variations in publication practices. Y1 - 2025 U6 - https://doi.org/10.51408/issi2025_204 ER - TY - JOUR A1 - Chen, Ying A1 - Koch, Thorsten A1 - Peng, Hanqui A1 - Zhang, Hongrui T1 - Benchmarking of Quantum and Classical Computing in Large-Scale Dynamic Portfolio Optimization Under Market Frictions Y1 - 2025 ER - TY - CHAP A1 - Turner, Mark A1 - Berthold, Timo A1 - Besançon, Mathieu T1 - A Context-Aware Cutting Plane Selection Algorithm for Mixed-Integer Programming T2 - Operations Research Proceedings 2023. OR 2023. N2 - The current cut selection algorithm used in mixed-integer programming solvers has remained largely unchanged since its creation. In this paper, we propose a set of new cut scoring measures, cut filtering techniques, and stopping criteria, extending the current state-of-the-art algorithm and obtaining a 5\% performance improvement for SCIP over the MIPLIB 2017 benchmark set. Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-58405-3_28 SP - 217 EP - 244 ER - TY - JOUR A1 - Shinano, Yuji A1 - Fujii, Koichi T1 - Introduction to Quadratic Programming Solvers JF - Journal of The Society of Instrument and Control Engineers Y1 - 2025 U6 - https://doi.org/10.11499/sicejl.64.532 VL - 64 IS - 8 SP - 532 EP - 540 ER - TY - JOUR A1 - Chen, Ying A1 - Xu, Xiuqin A1 - Koch, Thorsten T1 - Day-ahead high-resolution forecasting of natural gas demand and supply in Germany with a hybrid model JF - Applied Energy N2 - As the natural gas market is moving towards short-term planning, accurate and robust short-term forecasts of the demand and supply of natural gas is of fundamental importance for a stable energy supply, a natural gas control schedule, and transport operation on a daily basis. We propose a hybrid forecast model, Functional AutoRegressive and Convolutional Neural Network model, based on state-of-the-art statistical modeling and artificial neural networks. We conduct short-term forecasting of the hourly natural gas flows of 92 distribution nodes in the German high-pressure gas pipeline network, showing that the proposed model provides nice and stable accuracy for different types of nodes. It outperforms all the alternative models, with an improved relative accuracy up to twofold for plant nodes and up to fourfold for municipal nodes. For the border nodes with rather flat gas flows, it has an accuracy that is comparable to the best performing alternative model. KW - Natural gas flow forecasting KW - Neural network KW - Hybrid model KW - Functional autoregressive Y1 - 2020 U6 - https://doi.org/https://doi.org/10.1016/j.apenergy.2019.114486 VL - 262 IS - 114486 ER - TY - GEN A1 - Zakiyeva, Nazgul A1 - Petkovic, Milena T1 - High-dimensional high-frequency time series prediction with a mixed integer optimisation method T2 - Operations Research Proceedings T3 - ZIB-Report - 23-30 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-93114 SN - 1438-0064 ER - TY - THES A1 - Turner, Mark T1 - Cutting Plane Selection for Mixed-Integer Linear Programming N2 - Mixed-Integer Linear Programming (MILP) is a ubiquitous and practical modelling paradigm that is essential for optimising a broad range of real-world systems. The backbone of all modern MILP solvers is the branch-and-cut algorithm, which is a hybrid of the branch-and-bound and cutting planes algorithms. Cutting planes (cuts) are linear inequalities that tighten the relaxation of a MILP. While a lot of research has gone into deriving valid cuts for MILPs, less emphasis has been put on determining which cuts to select. Cuts in general are generated in rounds, and a subset of the generated cuts must be added to the relaxation. The decision on which subset of cuts to add is called cut selection. This is a crucial task since adding too many cuts makes the relaxation large and slow to optimise over. Conversely, adding too few cuts results in an insufficiently tightened relaxation, and more relaxations need to be enumerated. To further emphasise the difficulty, the effectiveness of an applied cut is both dependent on the other applied cuts, and the state of the MILP solver. In this thesis, we present theoretical results on the importance and difficulty of cut selection, as well as practical results that use cut selection to improve general MILP solver performance. Improving general MILP solver performance is of great importance for practitioners and has many runoff effects. Reducing the solve time of currently solved systems can directly improve efficiency within the application area. In addition, improved performance enables larger systems to be modelled and optimised, and MILP to be used in areas where it was previously impractical due to time restrictions. Each chapter of this thesis corresponds to a publication on cut selection, where the contributions of this thesis can naturally be divided into four components. The first two components are motivated by instance-dependent performance. In practice, for each subroutine, including cut selection, MILP solvers have adjustable parameters with hard-coded default values. It is ultimately unrealistic to expect these default values to perform well for every instance. Rather, it would be ideal if the parameters were dependent on the given instance. To show this motivation is well founded, we first introduce a family of parametric MILP instances and cuts to showcase worst-case performance of cut selection for any fixed parameter value. We then introduce a graph neural network architecture and reinforcement learning framework for learning instance-dependent cut scoring parameters. In the following component, we formalise language for determining if a cut has theoretical usefulness from a polyhedral point of view in relation to other cuts. In addition, to overcome issues of infeasible projections and dual degeneracy, we introduce analytic center based distance measures. We then construct a lightweight multi-output regression model that predicts relative solver performance of an instance for a set of distance measures. The final two components are motivated by general MILP solver improvement via cut selection. Such improvement was shown to be possible, albeit difficult to achieve, by the first half of this thesis. We relate branch-and-bound and cuts through their underlying disjunctions. Using a history of previously computed Gomory mixed-integer cuts, we reduce the solve time of SCIP over the 67% of affected MIPLIB 2017 instances by 4%. In the final component, we introduce new cut scoring measures and filtering methods based on information from other MILP solving processes. The new cut selection techniques reduce the solve time of SCIP over the 97% of affected MIPLIB 2017 instances by 5%. KW - Mixed-Integer Programming KW - Cutting Planes KW - Cut Selection KW - Machine Learning Y1 - 2024 ER - TY - JOUR A1 - Yueksel-Erguen, Inci A1 - Most, Dieter A1 - Wyrwoll, Lothar A1 - Schmitt, Carlo A1 - Zittel, Janina T1 - Modeling the transition of the multimodal pan-European energy system including an integrated analysis of electricity and gas transport JF - Energy Systems N2 - Most recently, the European energy system has undergone a fundamental transformation to meet decarbonization targets without compromising the security of the energy supply. The transition involves several energy-generating and consuming sectors emphasizing sector coupling. The increase in the share of renewable energy sources has revealed the need for flexibility in supporting the electricity grid to cope with the resulting high degree of uncertainty. The new technologies accompanying the energy system transition and the recent political crisis in Europe threatening the security of the energy supply have invalidated the experience from the past by drastically changing the conventional scenarios. Hence, supporting strategic planning tools with detailed operational energy network models with appropriate mathematical precision has become more important than ever to understand the impacts of these disruptive changes. In this paper, we propose a workflow to investigate optimal energy transition pathways considering sector coupling. This workflow involves an integrated operational analysis of the electricity market, its transmission grid, and the gas grid in high spatio-temporal resolution. Thus, the workflow enables decision-makers to evaluate the reliability of high-level models even in case of disruptive events. We demonstrate the capabilities of the proposed workflow using results from a pan-European case study. The case study, spanning 2020-2050, illustrates that feasible potential pathways to carbon neutrality are heavily influenced by political and technological constraints. Through integrated operational analysis, we identify scenarios where strategic decisions become costly or infeasible given the existing electricity and gas networks. Y1 - 2023 U6 - https://doi.org/10.1007/s12667-023-00637-5 ER - TY - JOUR A1 - Tjusila, Gennesaret A1 - Besançon, Mathieu A1 - Turner, Mark A1 - Koch, Thorsten T1 - How Many Clues To Give? A Bilevel Formulation For The Minimum Sudoku Clue Problem JF - Operations Research Letters N2 - It has been shown that any 9 by 9 Sudoku puzzle must contain at least 17 clues to have a unique solution. This paper investigates the more specific question: given a particular completed Sudoku grid, what is the minimum number of clues in any puzzle whose unique solution is the given grid? We call this problem the Minimum Sudoku Clue Problem (MSCP). We formulate MSCP as a binary bilevel linear program, present a class of globally valid inequalities, and provide a computational study on 50 MSCP instances of 9 by 9 Sudoku grids. Using a general bilevel solver, we solve 95% of instances to optimality, and show that the solution process benefits from the addition of a moderate amount of inequalities. Finally, we extend the proposed model to other combinatorial problems in which uniqueness of the solution is of interest. Y1 - 2024 U6 - https://doi.org/10.1016/j.orl.2024.107105 VL - 54 SP - 107105 ER - TY - JOUR A1 - Vanaret, Charlie T1 - Interval constraint programming for globally solving catalog-based categorical optimization JF - Journal of Global Optimization N2 - In this article, we propose an interval constraint programming method for globally solving catalog-based categorical optimization problems. It supports catalogs of arbitrary size and properties of arbitrary dimension, and does not require any modeling effort from the user. A novel catalog-based contractor (or filtering operator) guarantees consistency between the categorical properties and the existing catalog items. This results in an intuitive and generic approach that is exact, rigorous (robust to roundoff errors) and can be easily implemented in an off-the-shelf interval-based continuous solver that interleaves branching and constraint propagation. We demonstrate the validity of the approach on a numerical problem in which a categorical variable is described by a two-dimensional property space. A Julia prototype is available as open-source software under the MIT license. Y1 - 2024 U6 - https://doi.org/10.1007/s10898-023-01362-0 VL - 89 SP - 457 EP - 476 ER - TY - JOUR A1 - Le, Thi Thai A1 - Tran, Van Cuc A1 - Phung, Dang Hieu T1 - Numerical simulation of tidal flow in Danang Bay Based on non-hydrostatic shallow water equations JF - Pacific Journal of Mathematics for Industry N2 - This paper presents a numerical simulation of the tidal flow in Danang Bay (Vietnam) based on the non-hydrostatic shallow water equations. First, to test the simulation capability of the non-hydrostatic model, we have made a test simulation comparing it with the experiment by Beji and Battjes 1993. Simulation results for this case are compared with both the experimental data and calculations obtained from the traditional hydrostatic model. It is shown that the non-hydrostatic model is better than the hydrostatic model when the seabed topography variation is complex. The usefulness of the non-hydrostatic model is father shown by successfully simulating the tidal flow of Danang Bay. Y1 - 2016 U6 - https://doi.org/10.1186/s40736-015-0020-6 VL - 8 IS - 1 ER - TY - JOUR A1 - Hennings, Felix A1 - Hoppmann-Baum, Kai A1 - Zittel, Janina T1 - Optimizing transient gas network control for challenging real-world instances using MIP-based heuristics JF - Open Journal of Mathematical Optimization Y1 - 2024 U6 - https://doi.org/10.5802/ojmo.29 VL - 5 ER - TY - CHAP A1 - Pedersen, Jaap A1 - Ljubić, Ivana ED - Pardalos, Panos M. ED - Prokopyev, Oleg A. T1 - Prize-Collecting Steiner Tree Problem and its Variants T2 - Encyclopedia of Optimization Y1 - 2024 U6 - https://doi.org/10.1007/978-3-030-54621-2_869-1 PB - Springer International Publishing CY - Cham ER - TY - GEN 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. T3 - ZIB-Report - 23-17 KW - cutting plane selection KW - variable selection KW - mixed-integer programming Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-91120 SN - 1438-0064 ER - TY - GEN A1 - Turner, Mark A1 - Berthold, Timo A1 - Besançon, Mathieu T1 - A Context-Aware Cutting Plane Selection Algorithm for Mixed-Integer Programming N2 - The current cut selection algorithm used in mixed-integer programming solvers has remained largely unchanged since its creation. In this paper, we propose a set of new cut scoring measures, cut filtering techniques, and stopping criteria, extending the current state-of-the-art algorithm and obtaining a 5\% performance improvement for SCIP over the MIPLIB 2017 benchmark set. T3 - ZIB-Report - 23-21 KW - cutting plane selection KW - mixed-integer programming Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-91691 SN - 1438-0064 ER - TY - JOUR A1 - Le, Thi Thai A1 - Fukumoto, Yasuhide A1 - Koch, Thorsten T1 - Linear stability of a simple shear layer between two parallel streams in a shallow water flow JF - Physics Letters A N2 - The stability of shear layers in fluid flows is a crucial factor in forming vortices and jets and plays a fundamental role in the development of turbulence. Such shear layer instabilities are ubiquitous in natural phenomena, such as atmospheric and oceanic flows, contributing to the formation of weather systems and predicting tsunamis. This study specifically focuses on the stability of a shear layer sandwiched between two semi-infinite layers within a two-dimensional flow. The velocity profile of the shear layer is assumed to be linearly dependent on the vertical coordinate, while the velocity of the other layers remains uniform with differing strengths. The effect of viscosity and surface tension is ignored to simplify the analysis. The shallow water equations are used to analyze the interface stability of the shear layer, and the resulting dispersion relation between wave frequency and other wave characteristics is obtained. This relation incorporates Whittaker functions and their first derivatives and is used to derive appropriate limits corresponding to various physical conditions. Our study thus contributes to a deeper understanding of the stability of shear layers and their implications for natural phenomena. Y1 - 2024 U6 - https://doi.org/10.1016/j.physleta.2023.129264 VL - 493 PB - Elservier ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - An effective approach for deriving and evaluating approximate optimal design solutions of energy supply systems by time series aggregation JF - Frontiers in Energy Research N2 - It is important to design multi-energy supply systems optimally in consideration of their operations for variations in energy demands. An approach for efficiently solving such an optimal design problem with a large number of periods for variations in energy demands is to derive an approximate optimal design solution by time series aggregation. However, such an approach does not provide any information on the accuracy for the optimal value of the objective function. In this paper, an effective approach for time series aggregation is proposed to derive an approximate optimal design solution and evaluate a proper gap between the upper and lower bounds for the optimal value of the objective function based on a mixed-integer linear model. In accordance with aggregation, energy demands are relaxed to uncertain parameters and the problem for deriving an approximate optimal design solution and evaluating it is transformed to a three-level optimization problem, and it is solved by applying both the robust and hierarchical optimization methods. A case study is conducted on a cogeneration system with a practical configuration, and it turns out that the proposed approach enables one to derive much smaller gaps as compared with those obtained by a conventional approach. Y1 - 2023 U6 - https://doi.org/10.3389/fenrg.2023.1128681 VL - 11 SP - 1 EP - 14 ER - TY - GEN A1 - Pedersen, Jaap A1 - Weinand, Jann Michael A1 - Syranidou, Chloi A1 - Rehfeldt, Daniel T1 - An efficient solver for multi-objective onshore wind farm siting and network integration N2 - Existing planning approaches for onshore wind farm siting and network integration often do not meet minimum cost solutions or social and environmental considerations. In this paper, we develop an approach for the multi-objective optimization of turbine locations and their network connection using a Quota Steiner tree problem. Applying a novel transformation on a known directed cut formulation, reduction techniques, and heuristics, we design an exact solver that makes large problem instances solvable and outperforms generic MIP solvers. Although our case studies in selected regions of Germany show large trade-offs between the objective criteria of cost and landscape impact, small burdens on one criterion can significantly improve the other criteria. In addition, we demonstrate that contrary to many approaches for exclusive turbine siting, network integration must be simultaneously optimized in order to avoid excessive costs or landscape impacts in the course of a wind farm project. Our novel problem formulation and the developed solver can assist planners in decision making and help optimize wind farms in large regions in the future. T3 - ZIB-Report - 23-10 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-90590 SN - 1438-0064 ER - TY - GEN A1 - Tjusila, Gennesaret A1 - Besancon, Mathieu A1 - Turner, Mark A1 - Koch, Thorsten T1 - How Many Clues To Give? A Bilevel Formulation For The Minimum Sudoku Clue Problem N2 - It has been shown that any 9 by 9 Sudoku puzzle must contain at least 17 clues to have a unique solution. This paper investigates the more specific question: given a particular completed Sudoku grid, what is the minimum number of clues in any puzzle whose unique solution is the given grid? We call this problem the Minimum Sudoku Clue Problem (MSCP). We formulate MSCP as a binary bilevel linear program, present a class of globally valid inequalities, and provide a computational study on 50 MSCP instances of 9 by 9 Sudoku grids. Using a general bilevel solver, we solve 95\% of instances to optimality, and show that the solution process benefits from the addition of a moderate amount of inequalities. Finally, we extend the proposed model to other combinatorial problems in which uniqueness of the solution is of interest. T3 - ZIB-Report - 23-15 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-90902 ER - TY - THES A1 - Hennings, Felix T1 - Modeling and solving real-world transient gas network transport problems using mathematical programming N2 - This thesis considers the transient gas network control optimization problem for on-shore pipeline-based transmission networks with numerous gas routing options. As input, the problem is given the network's topology, its initial state, and future demands at the boundaries of the network, which prescribe the gas flow exchange and potentially the pressure values. The task is to find a set of future control measures for all the active, i.e., controllable, elements in the network that minimizes a combination of different penalty functions. The problem is examined in the context of a decision support tool for gas network dispatchers. This results in detailed models featuring a diverse set of constraints, large and challenging real-world instances, and demanding time limit requirements. All these factors further complicate the problem, which is already difficult to solve in theory due to the inherent combination of non-linear and combinatorial aspects. Our contributions concern different steps of the process of solving the problem. Regarding the model formulation, we investigate the validity of two common approximations of the gas flow description in transport pipes: neglecting the inertia term and assuming a friction term that linearly depends on the gas flow and the pressure. For both, we examine if they can be applied under real-world conditions by evaluating a large amount of historical state data of the network of our project partner, the gas network operator Open Grid Europe. While we can confirm that it is reasonable to ignore the influence of the inertia term, the friction term linearization leads to significant errors and, as a consequence, cannot be used for describing the general gas flow behavior in transport pipes. As another topic of this thesis, we introduce the target value concept as a more realistic approach to express control actions of dispatchers regarding regulators and compressor stations. Here, we derive the mechanisms defined for target values based on the gas flow principles in pipes and develop a mixed-integer programming model capturing their behavior. The accuracy of this model is demonstrated in comparison to a target-value-based industry-standard simulator. Furthermore, we present two heuristics for the transient gas network control optimization problem featuring target values that are based on approximative models for the target-value-based control and determine the final decisions in a post-processing step. To compare the performance of the two heuristics with the approach of directly solving the corresponding model, we evaluate them on a set of artificially created test instances. Finally, we develop problem-specific algorithms for two variants of the described problem. One considers the control optimization for a single network station, which represents a local operation site featuring a large number of active elements. The used transient model is very detailed and includes a sophisticated representation of the compressor stations. Based on the shortness of the pipes in the station, the corresponding algorithm finds valid solutions by solving a series of stationary model variants as well as a transient rolling horizon approach. As the second variant, we consider the problem on the entire network but assume an approximative model representing the control capabilities of network stations. Aside from a new description of the compression capabilities, we introduce an algorithm that uses a combination of sequential mixed-integer programming, two heuristics based on reduced time horizons, and a specialized dynamic branch-and-bound node limit to determine promising values for the binary variables of the model. Complete solutions for the problem are obtained by fixing the binary values and solving the remaining non-linear program. Both algorithms are investigated in extensive empirical studies based on real-world instances of the corresponding model variants. N2 - Diese Arbeit behandelt das Optimierungsproblem der transienten Gasnetzwerksteuerung von Fernleitungsnetzen auf dem Festland mit einer großen Anzahl möglicher Gastransportrouten. Die Eingabedaten bestehen aus der Netzwerktopologie, dem Anfangszustand des Netzes und zukünftigen Vorgaben an den Randknoten des Netzes, welche den Gaseinfluss und Gasausfluss sowie eine potenzielle Vorgabe von Druckwerten umfassen. Gegeben diese Daten besteht die Aufgabe besteht darin, eine Menge an zukünftigen Steuerungsentscheidungen für alle aktiven, also steuerbaren, Elemente des Netzes zu finden, sodass eine Kombination von Straffunktionen minimiert wird. Das Problem wird in dieser Arbeit im Rahmen der Erstellung eines entscheidungsunterstützenden Systems für Dispatcher betrachtet, welche das Gasnetz steuern. Dies resultiert in einer detaillierten Modellierung mit einer Vielzahl von Nebenbedingungen, großen und herausfordernden realistischen Instanzen sowie anspruchsvollen Vorgaben zur maximalen Laufzeit. Diese Eigenschaften erhöhen die Komplexität des Problems, welches bereits in der Theorie auf Grund der inhärenten Kombination von nichtlinearen und kombinatorischen Aspekten schwierig zu lösen ist. Die Beiträge dieser Arbeit betreffen verschiedene Schritte des Prozesses zur Lösung des Problems. Bezüglich der Modellformulierung werden zwei übliche Approximationen der Gasflussbeschreibung in Fernleitungsrohren auf Validität überprüft: die Vernachlässigung des Trägheitsterms und die Annahme einer linearisierten Beschreibung des Reibungsterms. Für beide Approximationen wird untersucht, ob sie für reale Gasflussbedingungen zulässig sind. Dazu wird eine große Anzahl historischer Netzzustandsdaten des Gasnetzbetreibers Open Grid Europe ausgewertet. Während bestätigt werden kann, dass eine Vernachlässigung des Trägheitsterms unter Realbedingungen angemessen ist, führt die Linearisierung des Reibungsterms zu signifikanten Fehlern und kann daher nicht für die allgemeine Beschreibung des Gasflusses in Fernleitungsrohren verwendet werden. In einem weiteren Teil dieser Arbeit wird das Konzept der Sollwerte eingeführt. Mit diesen ist eine realistischere Beschreibung der Steuerungsbefehle möglich, welche den Dispatchern für Regler und Verdichterstationen zur Verfügung stehen. Der Sollwertmechanismus wird basierend auf den Gasflussprinzipien in Rohrleitungen hergeleitet, um anschließend ein gemischt-ganzzahliges Programm zu entwickeln, welches das entsprechende Verhalten erzeugt. Die Präzision dieses Modells wird durch einen Vergleich mit einem Simulator von Industriestandard sichergestellt, welcher auf Sollwerten basiert. Außerdem werden zwei Heuristiken für das Optimierungsproblem der transienten Gasnetzwerksteuerung mit Sollwertmodellierung vorgestellt. Diese basieren auf approximativen Modellen für die Sollwertsteuerung und ermitteln die letztendlichen Steuerungsentscheidungen in einer nachgelagerten Routine. Basierend auf künstlich erzeugten Testinstanzen werden die Heuristiken schließlich mit dem direkten Lösen des entsprechenden Modells verglichen. Zudem werden in dieser Arbeit problemspezifische Algorithmen für zwei Varianten des beschriebenen Optimierungsproblems entwickelt. Die erste Variante betrachtet das Gasnetzwerksteuerungsproblem beschränkt auf eine einzelne Netzstation, die lokale Betriebsstellen darstellen und über eine Vielzahl an aktiven Steuerungselementen verfügen. Das entsprechende transiente Modell ist sehr detailliert und beinhaltet eine differenzierte Beschreibung der Verdichterstationen. Der problemspezifische Algorithmus basiert auf der Kürze der Rohre innerhalb der Station und findet zulässige Lösungen durch das Lösen von stationären Varianten des Modells sowie der Nutzung eines transienten Rolling-Horizon Ansatzes. In der zweiten Problemvariante wird das gesamte Gasnetz betrachtet, wobei eine vereinfachte Modellierung der Steuerungsmöglichkeiten innerhalb von Netzstationen angenommen wird. Neben einer neuen Beschreibung der Verdichtungsmöglichkeiten einer Station wird ebenfalls ein problemspezifischer Algorithmus entwickelt. Dieser erstellt aussichtsreiche Werte für die Binärvariablen und nutzt dafür eine Kombination aus sequenzieller gemischt-ganzzahliger Programmierung, zwei auf verkürzten Zeithorizonten basierenden Heuristiken und eine spezialisierte dynamische Obergrenze für die Anzahl der Branch-and-Bound-Knoten. Diese Teillösungen werden durch eine Fixierung der binären Variablen und das anschließende Lösen des restlichen nichtlinearen Programms komplettiert. Die Güte beider Algorithmen wird in umfangreichen empirischen Experimenten untersucht, welche reale Instanzen der jeweiligen Problemvarianten betrachten. Y1 - 2023 ER - TY - JOUR A1 - Hennings, Felix A1 - Petkovic, Milena A1 - Streubel, Tom T1 - On the Numerical Treatment of Interlaced Target Values - Modeling, Optimization and Simulation of Regulating Valves in Gas Networks JF - Optimization and Engineering N2 - Due to the current and foreseeable shifts towards carbon dioxide neutral energy production, which will likely result in balancing fluctuating renewable energy generation by transforming power-to-gas-to-power as well as building a large-scale hydrogen transport infrastructure, the trading and transport operations of gas will become more dynamic, volatile, and hence also less predictable. Therefore, computer-aided support in terms of rapid simulation and control optimization will further broaden its importance for gas network dispatching. In this paper, we aim to contribute and openly publish two new mathematical models for regulators, also referred to as control valves, which together with compressors make up the most complex and involved types of active elements in gas network infrastructures. They provide direct control over gas networks but are in turn controlled via target values, also known as set-point values, themselves. Our models incorporate up to six dynamical target values to define desired transient states for the elements' local vicinity within the network. That is, each pair of every two target values defines a bounding box for the inlet pressure, outlet pressure as well as the passing mass flow of gas. In the proposed models, those target values are prioritized differently and are constantly in competition with each other, which can only be resolved dynamically at run-time of either a simulation or optimization process. Besides careful derivation, we compare simulation and optimization results with predictions of the widely adopted commercial simulation tool SIMONE, serving as our substitute for actual real-world transport operations. Y1 - 2024 U6 - https://doi.org/10.1007/s11081-023-09812-0 VL - 25 SP - 491 EP - 527 PB - Springer Nature ER - TY - JOUR A1 - 品野, 勇治 T1 - MIPLIB と Hans Mittelmann’s benchmarks JF - 機関誌「オペレーションズ・リサーチ」 N2 - 混合整数計画法 (Mixed Integer Programming: MIP) は,MIP を解くソフトウェアである MIP ソルバが大規模な現実問題を解けるようになったこともあり,現実問題を解く有用な OR の手法として広く知られるようになった.しかしながら,MIP ソルバの開発に欠かせないベンチマーク・データセットおよび性能測定方法についてはそれほど広く知られているとは言い難い.ベンチマーク・データセットは注意を払って作成しないと,多くのバイアスがかかってしまう.それらのバイアスを可能な限りのぞき,真に有用なベンチマーク・テストの結果を得るためには複数の人数で多大な労力を割く必要がある.本稿では,そのような MIP ソルバ開発の背景として重要な役割を果たしてきた MIPLIB と Hans Mittelmann’s benchmarks について解説する.また,本稿において Hans Mittelmann’s benchmarks は,BENCHMARKS FOR OPTIMIZATION SOFTWAREのページ (http://plato.asu.edu/bench.html) に示されているベンチマークである. Y1 - 2020 UR - https://orsj.org/wp-content/corsj/or65-1/or65_1_49.pdf VL - 65 IS - 1 SP - 49 EP - 56 ER - TY - JOUR A1 - 品野, 勇治 A1 - 藤井, 浩一 T1 - 使ってみよう線形計画ソルバ JF - 機関誌「オペレーションズ・リサーチ」 N2 - 本稿では,線形計画問題を解くソフトウェアである線形計画ソルバの標準的な利用方法と,原稿執筆時点で利用可能なソルバを可能な限り紹介する.筆者らはソルバ開発コミュニティの中で仕事をしているので,この機会に現在のソルバ開発現場の様子も紹介するとともに,各ソルバの特徴として何を紹介するべきかは,できる限り開発者,または,開発者に近い研究者に問い合わせて記述した.本稿は,多くの線形計画ソルバの選択肢がある中で,読者がもつ問題を解くのに最も適当なソルバを選択するための指針を与えることを主たる目的としている. Y1 - 2019 UR - https://orsj.org/wp-content/corsj/or64-4/or64_4_238.pdf VL - 64 IS - 4 SP - 238 EP - 245 ER - TY - CHAP A1 - Petkovic, Milena A1 - Zittel, Janina T1 - Forecasting and modeling the dynamics of large-scale energy networks under the supply and demand balance constraint T2 - Optimization in Green Sustainability and Ecological Transition. ODS 2023 N2 - With the emergence of ”Big Data” the analysis of large data sets of high-dimensional energy time series in network structures have become feasible. However, building large-scale data-driven and computationally efficient models to accurately capture the underlying spatial and temporal dynamics and forecast the multivariate time series data remains a great challenge. Additional constraints make the problem more challenging to solve with conventional methods. For example, to ensure the security of supply, energy networks require the demand and supply to be balanced. This paper introduces a novel large-scale Hierarchical Network Regression model with Relaxed Balance constraint (HNR-RB) to investigate the network dynamics and predict multistep-ahead flows in the natural gas transmission network, where the total in- and out-flows of the network have to be balanced over a period of time. We concurrently address three main challenges: high dimensionality of networks with more than 100 nodes, unknown network dynamics, and constraint of balanced supply and demand in the network. The effectiveness of the proposed model is demonstrated through a real-world case study of forecasting demand and supply in a large-scale natural gas transmission network. The results demonstrate that HNR-RB outperforms alternative models for short- and mid-term horizons. Y1 - 2024 U6 - https://doi.org/10.1007/978-3-031-47686-0_29 VL - 12 ER - TY - JOUR A1 - Tateiwa, Nariaki A1 - Shinano, Yuji A1 - Yasuda, Masaya A1 - Kaji, Shizuo A1 - Yamamura, Keiichiro A1 - Fujisawa, Katsuki T1 - Development and analysis of massive parallelization of a lattice basis reduction algorithm JF - Japan Journal of Industrial and Applied Mathematics N2 - The security of lattice-based cryptography relies on the hardness of solving lattice problems. Lattice basis reduction is a strong tool for solving lattice problems, and the block Korkine–Zolotarev (BKZ) reduction algorithm is the de facto standard in cryptanalysis. We propose a parallel algorithm of BKZ-type reduction based on randomization. Randomized copies of an input lattice basis are independently reduced in parallel, while several basis vectors are shared asynchronously among all processes. There is a trade-off between randomization and information sharing; if a substantial amount of information is shared, all processes might work on the same problem, which diminishes the benefit of parallelization. To monitor the balance between randomness and sharing, we propose a new metric to quantify the variety of lattice bases, and we empirically find an optimal parameter of sharing for high-dimensional lattices. We also demonstrate the effectiveness of our parallel algorithm and metric through experiments from multiple perspectives. Y1 - 2023 U6 - https://doi.org/10.1007/s13160-023-00580-z VL - 40 IS - 1 SP - 13 EP - 56 ER - TY - GEN A1 - Prause, Felix A1 - Hoppmann-Baum, Kai A1 - Defourny, Boris A1 - Koch, Thorsten T1 - The Maximum Diversity Assortment Selection Problem N2 - In this paper, we introduce the Maximum Diversity Assortment Selection Problem (MADASS), which is a generalization of the 2-dimensional Cutting Stock Problem (2CSP). Given a set of rectangles and a rectangular container, the goal of 2CSP is to determine a subset of rectangles that can be placed in the container without overlapping, i.e., a feasible assortment, such that a maximum area is covered. In MADASS, we need to determine a set of feasible assortments, each of them covering a certain minimum threshold of the container, such that the diversity among them is maximized. Thereby, diversity is defined as minimum or average normalized Hamming-Distance of all assortment pairs. The MADASS Problem was used in the 11th AIMMS-MOPTA Competition in 2019. The methods we describe in this article and the computational results won the contest. In the following, we give a definition of the problem, introduce a mathematical model and solution approaches, determine upper bounds on the diversity, and conclude with computational experiments conducted on test instances derived from the 2CSP literature. T3 - ZIB-Report - 20-34 KW - Combinatorial Optimization KW - Mixed Integer Programming KW - 2-dim Cutting Stock Problem KW - Maximum Diversity Problem Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-81039 SN - 1438-0064 ER - TY - GEN A1 - Anderson, Lovis A1 - Turner, Mark A1 - Koch, Thorsten T1 - Generative deep learning for decision making in gas networks N2 - A decision support system relies on frequent re-solving of similar problem instances. While the general structure remains the same in corresponding applications, the input parameters are updated on a regular basis. We propose a generative neural network design for learning integer decision variables of mixed-integer linear programming (MILP) formulations of these problems. We utilise a deep neural network discriminator and a MILP solver as our oracle to train our generative neural network. In this article, we present the results of our design applied to the transient gas optimisation problem. With the trained network we produce a feasible solution in 2.5s, use it as a warm-start solution, and thereby decrease global optimal solution solve time by 60.5%. T3 - ZIB-Report - 20-38 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-81103 SN - 1438-0064 ER - TY - GEN A1 - Petkovic, Milena A1 - Koch, Thorsten A1 - Zittel, Janina T1 - Deep learning for spatio-temporal supply and demand forecasting in natural gas transmission networks N2 - Germany is the largest market for natural gas in the European Union, with an annual consumption of approx. 95 billion cubic meters. Germany's high-pressure gas pipeline network is roughly 40,000 km long, which enables highly fluctuating quantities of gas to be transported safely over long distances. Considering that similar amounts of gas are also transshipped through Germany to other EU states, it is clear that Germany's gas transport system is essential to the European energy supply. Since the average velocity of gas in a pipeline is only 25km/h, an adequate high-precision, high-frequency forecasting of supply and demand is crucial for efficient control and operation of such a transmission network. We propose a deep learning model based on spatio-temporal convolutional neural networks (DLST) to tackle the problem of gas flow forecasting in a complex high-pressure transmission network. Experiments show that our model effectively captures comprehensive spatio-temporal correlations through modeling gas networks and consistently outperforms state-of-the-art benchmarks on real-world data sets by at least 21$\%$. The results demonstrate that the proposed model can deal with complex nonlinear gas network flow forecasting with high accuracy and effectiveness. T3 - ZIB-Report - 21-01 Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-81221 SN - 1438-0064 ER - TY - JOUR A1 - Zakiyeva, Nazgul A1 - Xu, X. T1 - Nonlinear network autoregressive model with application to natural gas network forecasting JF - Mathematics Japonica T3 - ZIB-Report - 21-24 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-81025 ER - TY - JOUR A1 - Streubel, Tom A1 - Tischendorf, Caren A1 - Griewank, Andreas T1 - Piecewise Polynomial Taylor Expansions - The Generalization of Faà di Bruno's Formula JF - Modeling, Simulation and Optimization of Complex Processes HPSC 2018 N2 - We present an extension of Taylor's Theorem for the piecewise polynomial expansion of non-smooth evaluation procedures involving absolute value operations. Evaluation procedures are computer programs of mathematical functions in closed form expression and allow a different treatment of smooth operations or calls to the absolute value function. The well known classical Theorem of Taylor defines polynomial approximations of sufficiently smooth functions and is widely used for the derivation and analysis of numerical integrators for systems of ordinary differential- or differential-algebraic equations, for the construction of solvers for continuous non-linear optimization of finite dimensional objective functions and for root solving of non-linear systems of equations. The long term goal is the stabilization and acceleration of already known methods and the derivation of new methods by incorporating piecewise polynomial Taylor expansions. The herein provided proof of the higher order approximation quality of the new generalized expansions is constructive and allows efficiently designed algorithms for the execution and computation of the piecewise polynomial expansions. As a demonstration towards the ultimate goal we will derive a prototype of a {\$}{\$}k{\$}{\$}k-step method on the basis of polynomial interpolation and the proposed generalized expansions. Y1 - 2020 U6 - https://doi.org/10.1007/978-3-030-55240-4_3 IS - Modeling, Simulation and Optimization of Complex Processes HPSC 2018 SP - 63 EP - 82 PB - Springer International Publishing ER - TY - JOUR A1 - Le, Thi Thai A1 - Koch, Thorsten T1 - Instability of a tangential discontinuity surface in a three-dimensional compressible medium JF - Physics of Fluids N2 - Compressible flows appear in many natural and technological processes, for instance, the flow of natural gases in a pipe system. Thus, a detailed study of the stability of tangential velocity discontinuity in compressible media is relevant and necessary. The first early investigation in two-dimensional (2D) media was given more than 70 years ago. In this article, we continue investigating the stability in three-dimensional (3D) media. The idealized statement of this problem in an infinite spatial space was studied by Syrovatskii in 1954. However, the omission of the absolute sign of cos θ with θ being the angle between vectors of velocity and wave number in a certain inequality produced the inaccurate conclusion that the flow is always unstable for entire values of the Mach number M. First, we revisit this case to arrive at the correct conclusion, namely that the discontinuity surface is stabilized for a large Mach number with a given value of the angle θ. Next, we introduce a real finite spatial system such that it is bounded by solid walls along the flow direction. We show that the discontinuity surface is stable if and only if the dispersion relation equation has only real roots, with a large value of the Mach number; otherwise, the surface is always unstable. In particular, we show that a smaller critical value of the Mach number is required to make the flow in a narrow channel stable. Y1 - 2021 U6 - https://doi.org/10.1063/5.0033753 VL - 33 IS - 1 SP - 016106 ER - TY - JOUR A1 - Hoppmann-Baum, Kai A1 - Hennings, Felix A1 - Zittel, Janina A1 - Gotzes, Uwe A1 - Spreckelsen, Eva-Maria A1 - Spreckelsen, Klaus A1 - Koch, Thorsten T1 - An Optimization Approach for the Transient Control of Hydrogen Transport Networks JF - Mathematical Methods of Operations Research Y1 - 2021 IS - Special Issue on Energy Networks ER - TY - GEN A1 - Hoppmann-Baum, Kai A1 - Mexi, Gioni A1 - Burdakov, Oleg A1 - Casselgren, Carl Johan A1 - Koch, Thorsten T1 - Length-Constrained Cycle Partition with an Application to UAV Routing N2 - In this article, we discuss the Length-Constrained Cycle Partition Problem (LCCP). Besides edge weights, the undirected graph in LCCP features an individual critical weight value for each vertex. A cycle partition, i.e., a vertex disjoint cycle cover, is a feasible solution if the length of each cycle is not greater than the critical weight of each of the vertices in the cycle. The goal is to find a feasible partition with the minimum number of cycles. In this article, we discuss theoretical properties, preprocessing techniques, and two mixed-integer programming models (MIP) for LCCP both inspired by formulations for the closely related Travelling Salesperson Problem (TSP). Further, we introduce conflict hypergraphs, whose cliques yield valid constraints for the MIP models. We conclude with a report on computational experiments conducted on (A)TSPLIB-based instances. As an example, we use a routing problem in which a fleet of uncrewed aerial vehicles (UAVs) patrols a set of areas. T3 - ZIB-Report - 20-30 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-80489 SN - 1438-0064 ER - TY - CHAP A1 - Yokoyama, Ryohei A1 - Kamada, Hiroki A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - A Hierarchical Optimization Approach to Robust Design of Energy Supply Systems Based on a Mixed-Integer Linear Model T2 - Conference N2 - In designing energy supply systems, designers should heighten the robustness in performance criteria against the uncertainty in energy demands. In this paper, a robust optimal design method using a hierarchi- cal mixed-integer linear programming (MILP) method is proposed to maximize the robustness of energy sup- ply systems under uncertain energy demands based on a mixed-integer linear model. A robust optimal design problem is formulated as a three-level min-max-min MILP one by expressing uncertain energy demands by intervals, evaluating the robustness in a performance criterion based on the minimax regret cri- terion, and considering relationships among integer design variables, uncertain energy demands, and inte- ger and continuous operation variables. This problem is solved by evaluating upper and lower bounds for the minimum of the maximum regret of the performance criterion repeatedly outside, and evaluating lower and upper bounds for the maximum regret repeatedly inside. Since these different types of optimization problems are difficult to solve even using commercial MILP solvers, they are solved by applying a hierarchi- cal MILP method developed for ordinary optimal design problems with its modifications. In a case study, the proposed approach is applied to the robust optimal design of a cogeneration system. Through the study, its validity and effectiveness are ascertained, and some features of the obtained robust designs are clarified. Y1 - 2020 SP - 601 EP - 613 ER - TY - CHAP A1 - Yokoyama, Ryohei A1 - Takeuchi, Kotaro A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - Effect of Model Reduction by Time Aggregation in Multiobjective Optimal Design of Energy Supply Systems by a Hierarchical MILP Method T2 - Conference N2 - The mixed-integer linear programming (MILP) method has been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems effi- ciently. As one of the strategies to enhance the computation efficiency furthermore, a method of reducing model by time aggregation has been proposed to search design candidates accurately and efficiently in the relaxed optimal design problem at the upper level. In this paper, the hierarchical MILP method and model reduction by time aggregation are applied to the multiobjective optimal design. In applying the model reduc- tion, the methods of clustering periods by the order of time series, based on an operational strategy, and by the k-medoids method are applied. As a case study, the multiobjective optimal design of a gas turbine cogeneration system with a practical configuration is investigated by adopting the annual total cost and pri- mary energy consumption as the objective functions to be minimized simultaneously, and the clustering methods are compared with one another in terms of the computation efficiency. It turns out that the model reduction by any clustering method is effective to enhance the computation efficiency when importance is given to minimizing the first objective function. It also turns out that the model reduction only by the k- medoids method is effective very limitedly when importance is given to minimizing the second objective function. Y1 - 2020 SP - 627 EP - 639 ER - TY - JOUR A1 - Gotzes, Uwe A1 - Hoppmann-Baum, Kai T1 - Bounding the final rank during a round robin tournament with integer programming JF - Operational Research N2 - This article is mainly motivated by the urge to answer two kinds of questions regarding the Bundesliga, which is Germany’s primary football (soccer) division having the highest average stadium attendance worldwide: “At any point in the season, what is the lowest final rank a certain team can achieve?” and “At any point in the season, what is the highest final rank a certain team can achieve?”. Although we focus on the Bundesliga in particular, the integer programming formulations we introduce to answer these questions can easily be adapted to a variety of other league systems and tournaments. Y1 - 2020 U6 - https://doi.org/https://doi.org/10.1007/s12351-020-00546-w VL - 1866-1505 ER - TY - JOUR A1 - Koch, Thorsten A1 - Schmidt, Martin A1 - Hiller, Benjamin A1 - Pfetsch, Marc A1 - Geißler, Björn A1 - Henrion, René A1 - Joormann, Imke A1 - Martin, Alexander A1 - Morsi, Antonio A1 - Römisch, Werner A1 - Schewe, Lars A1 - Schultz, Rüdiger T1 - Capacity Evaluation for Large-Scale Gas Networks JF - German Success Stories in Industrial Mathematics Y1 - 2020 SN - 978-3-030-81454-0 U6 - https://doi.org/10.1007/978-3-030-81455-7 VL - 35 SP - 23 EP - 28 ER - TY - JOUR A1 - Chen, Ying A1 - Zakiyeva, Nazgul A1 - Zhu, Bangzhu A1 - Koch, Thorsten T1 - Modeling and Forecasting the Dynamics of the Natural Gas Transmission Network in Germany with the Demand and Supply Balance Constraint JF - Applied Energy Y1 - 2020 U6 - https://doi.org/10.1016/j.apenergy.2020.115597 N1 - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3646636 IS - 278 ER - TY - JOUR A1 - Koch, Thorsten A1 - Chen, Ying A1 - Lim, Kian Guan A1 - Xu, Xiaofei A1 - Zakiyeva, Nazgul T1 - A review study of functional autoregressive models with application to energy forecasting JF - WIREs Computational Statistics Y1 - 2020 U6 - https://doi.org/10.1002/wics.1525 N1 - https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=7693&context=lkcsb_research ER - TY - CHAP A1 - Koch, Thorsten A1 - Rehfeldt, Daniel A1 - Shinano, Yuji T1 - An exact high performance solver for Steiner tree problems in graphs and related problems T2 - Modeling, Simulation and Optimization of Complex Processes HPSC 2018 Y1 - 2020 PB - Springer ER - TY - GEN A1 - Rehfeldt, Daniel A1 - Koch, Thorsten T1 - Implications, conflicts, and reductions for Steiner trees T3 - ZIB-Report - 20-28 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-80039 SN - 1438-0064 ER - TY - GEN A1 - Hoppmann-Baum, Kai A1 - Hennings, Felix A1 - Zittel, Janina A1 - Gotzes, Uwe A1 - Spreckelsen, Eva-Maria A1 - Spreckelsen, Klaus A1 - Koch, Thorsten T1 - From Natural Gas towards Hydrogen - A Feasibility Study on Current Transport Network Infrastructure and its Technical Control N2 - This study examines the usability of a real-world, large-scale natural gas transport infrastructure for hydrogen transport. We investigate whether a converted network can transport the amounts of hydrogen necessary to satisfy current energy demands. After introducing an optimization model for the robust transient control of hydrogen networks, we conduct computational experiments based on real-world demand scenarios. Using a representative network, we demonstrate that replacing each turbo compressor unit by four parallel hydrogen compressors, each of them comprising multiple serial compression stages, and imposing stricter rules regarding the balancing of in- and outflow suffices to realize transport in a majority of scenarios. However, due to the reduced linepack there is an increased need for technical and non-technical measures leading to a more dynamic network control. Furthermore, the amount of energy needed for compression increases by 364% on average. T3 - ZIB-Report - 20-27 KW - Hydrogen Transport KW - Hydrogen Infrastructure KW - Network Flows KW - Mixed Integer Programming KW - Energiewende Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-79901 SN - 1438-0064 ER - TY - JOUR A1 - Hoppmann-Baum, Kai A1 - Hennings, Felix A1 - Lenz, Ralf A1 - Gotzes, Uwe A1 - Heinecke, Nina A1 - Spreckelsen, Klaus A1 - Koch, Thorsten T1 - Optimal Operation of Transient Gas Transport Networks JF - Optimization and Engineering N2 - In this paper, we describe an algorithmic framework for the optimal operation of transient gas transport networks consisting of a hierarchical MILP formulation together with a sequential linear programming inspired post-processing routine. Its implementation is part of the KOMPASS decision support system, which is currently used in an industrial setting. Real-world gas transport networks are controlled by operating complex pipeline intersection areas, which comprise multiple compressor units, regulators, and valves. In the following, we introduce the concept of network stations to model them. Thereby, we represent the technical capabilities of a station by hand-tailored artificial arcs and add them to network. Furthermore, we choose from a predefined set of flow directions for each network station and time step, which determines where the gas enters and leaves the station. Additionally, we have to select a supported simple state, which consists of two subsets of artificial arcs: Arcs that must and arcs that cannot be used. The goal is to determine a stable control of the network satisfying all supplies and demands. The pipeline intersections, that are represented by the network stations, were initially built centuries ago. Subsequently, due to updates, changes, and extensions, they evolved into highly complex and involved topologies. To extract their basic properties and to model them using computer-readable and optimizable descriptions took several years of effort. To support the dispatchers in controlling the network, we need to compute a continuously updated list of recommended measures. Our motivation for the model presented here is to make fast decisions on important transient global control parameters, i.e., how to route the flow and where to compress the gas. Detailed continuous and discrete technical control measures realizing them, which take all hardware details into account, are determined in a subsequent step. In this paper, we present computational results from the KOMPASS project using detailed real-world data. Y1 - 2020 U6 - https://doi.org/10.1007/s11081-020-09584-x VL - 22 SP - 735 EP - 781 ER -