@article{JinLeFukumoto2019, author = {Jin, Liangbing and Le, Thi Thai and Fukumoto, Yasuhide}, title = {Frictional effect on stability of discontinuity interface in tangential velocity of a shallow-water flow}, volume = {383}, journal = {Physics Letters A}, number = {26}, doi = {10.1016/j.physleta.2019.125839}, pages = {125839}, year = {2019}, abstract = {We examine a frictional effect on the linear stability of an interface of discontinuity in tangential velocity. The fluid is moving with uniform velocity U in a region but is at rest in the other, and the bottom surface is assumed to exert drag force, quadratic in velocity, on the thin fluid layer. In the absence of the drag, the instability of the Kelvin-Helmholtz type is suppressed for U>√8 c, with c being the propagating speed of the gravity wave. We find by asymptotic analyses for both small and large values of the drag strength that the drag, regardless of its strength, makes the flow unstable for the whole range of the Froude number U/c.}, language = {en} } @misc{Lenz2021, author = {Lenz, Ralf}, title = {Pipe Merging for Transient Gas Network Problems}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-82116}, year = {2021}, abstract = {In practice, transient gas transport problems frequently have to be solved for large-scale gas networks. Gas network optimization problems typically belong to the class of Mixed-Integer Nonlinear Programming Problems (MINLP). However current state-of-the-art MINLP solvers are not yet mature enough to solve large-scale real-world instances. Therefore, an established approach in practice is to solve the problems with respect to a coarser representation of the network and thereby reducing the size of the underlying model. Two well-known aggregation methods that effectively reduce the network size are parallel and serial pipe merges. However, these methods have only been studied in stationary gas transport problems so far. This paper closes this gap and presents parallel and serial pipe merging methods in the context of transient gas transport. To this end, we introduce the concept of equivalent and heuristic subnetwork replacements. For the heuristic methods, we conduct a huge empirical evaluation based on real-world data taken from one of the largest gas networks in Europe. It turns out that both, parallel and serial pipe merging can be considered as appropriate aggregation methods for real-world transient gas flow problems.}, language = {en} } @article{RehfeldtHobbieSchoenheitetal.2022, author = {Rehfeldt, Daniel and Hobbie, Hannes and Sch{\"o}nheit, David and Koch, Thorsten and M{\"o}st, Dominik and Gleixner, Ambros}, title = {A massively parallel interior-point solver for LPs with generalized arrowhead structure, and applications to energy system models}, volume = {296}, journal = {European Journal of Operational Research}, number = {1}, doi = {10.1016/j.ejor.2021.06.063}, pages = {60 -- 71}, year = {2022}, abstract = {Linear energy system models are a crucial component of energy system design and operations, as well as energy policy consulting. If detailed enough, such models lead to large-scale linear programs, which can be intractable even for the best state-of-the-art solvers. This article introduces an interior-point solver that exploits common structures of energy system models to efficiently run in parallel on distributed-memory systems. The solver is designed for linear programs with doubly-bordered block-diagonal constraint matrix and makes use of a Schur complement based decomposition. In order to handle the large number of linking constraints and variables commonly observed in energy system models, a distributed Schur complement preconditioner is used. In addition, the solver features a number of more generic techniques such as parallel matrix scaling and structure-preserving presolving. The implementation is based on the solver PIPS-IPM. We evaluate the computational performance on energy system models with up to four billion nonzero entries in the constraint matrix—and up to one billion columns and one billion rows. This article mainly concentrates on the energy system model ELMOD, which is a linear optimization model representing the European electricity markets by the use of a nodal pricing market-clearing. It has been widely applied in the literature on energy system analyses in recent years. However, it will be demonstrated that the new solver is also applicable to other energy system models.}, language = {en} } @article{Le2019, author = {Le, Thi Thai}, title = {Kelvin-Helmholtz instability in a shallow-water flow with a finite width}, volume = {60}, journal = {Journal of Mathematical Physics}, number = {1}, publisher = {AIP Publishing}, doi = {10.1063/1.5126321}, pages = {123101}, year = {2019}, abstract = {We examine an effect of side walls on the linear stability of an interface of tangential-velocity discontinuity in shallow-water flow. The flow is pure horizontal in the plane xy, and the fluid is bounded in a finite width 2d in the y- direction. In region 0 < y < d, the fluid is moving with uniform velocity U but is at rest for -d < y < 0. Without side walls, the flow is unstable for a velocity difference U<√8c U < √8 c, with c being the velocity of gravity waves. In this work, we show that if the velocity difference U is smaller than 2c, the interface is always destabilized, also known as the flow is unstable. The unstable region of an infinite width model is shrunken by the effects of side walls in the case of narrow width, while there is no range for the Froude number for stabilization in the case of large width. These results play an important role in predicting the wave propagations and have a wide application in the fields of industry. As a result of the interaction of waves and the mean flow boundary, the flow is unstable, which is caused by a decrease in the kinetic energy of disturbance.}, language = {en} } @inproceedings{RehfeldtKoch2021, author = {Rehfeldt, Daniel and Koch, Thorsten}, title = {Implications, conflicts, and reductions for Steiner trees}, booktitle = {Integer Programming and Combinatorial Optimization: 22th International Conference, IPCO 2021}, doi = {10.1007/978-3-030-73879-2_33}, pages = {473 -- 487}, year = {2021}, language = {en} } @misc{Hennings2021, author = {Hennings, Felix}, title = {Large-scale empirical study on the momentum equation's inertia term}, issn = {1438-0064}, doi = {10.1016/j.jngse.2021.104153}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-81881}, year = {2021}, abstract = {A common approach to reduce the Euler equations' complexity for the simulation and optimization of gas networks is to neglect small terms that contribute little to the overall equations. An example is the inertia term of the momentum equation since it is said to be of negligible size under real-world operating conditions. However, this justification has always only been based on experience or single sets of artificial data points. This study closes this gap by presenting a large-scale empirical evaluation of the absolute and relative size of the inertia term when operating a real-world gas network. Our data consists of three years of fine-granular state data of one of the largest gas networks in Europe, featuring over 6,000 pipes with a total length of over 10,000 km. We found that there are only 120 events in which a subnetwork consisting of multiple pipes has an inertia term of high significance for more than three minutes. On average, such an event occurs less often than once every ten days. Therefore, we conclude that the inertia term is indeed negligible for real-world transient gas network control problems.}, language = {en} } @article{Le2021, author = {Le, Thi Thai}, title = {Effect of water depth on Kelvin - Helmholtz instability in a shallow-water flow}, volume = {62}, journal = {Journal of Mathematical Physics}, number = {10}, publisher = {AIP Publishing}, doi = {10.1063/1.5145060}, pages = {103101}, year = {2021}, abstract = {It is well known that the interface between two regions of an incompressible ideal fluid flow moving in a relative motion is necessarily destabilized, regardless of the velocity difference's strength. This phenomenon is the so-called Kelvin-Helmholtz instability (KHI). However, a large number of works demonstrated a surprising result that the instability is suppressed for shallow water flows; the interface is stabilized if the Froude number, defined by the velocity difference's ratio to the gravity wave's speed, is sufficiently large. In a limited way, these authors have been used the shallow-water equations without the higher-order effect of the dispersive terms. Thus, this investigation aims to examine these higher-order dispersive effects to analyze the interface stability problem of tangential-velocity discontinuity in shallow-water flows. In particular, we use the Green-Naghdi equations to introduce the dispersive terms related to the depth and the depth-averaged horizontal velocities of the fluid. We show that the interface stability depends on the Froude number (i.e., the velocity difference's strength) and the water depth. A critical value of the Froude number to stabilize the interface is smaller than the case of no dispersive terms, and the flow in a deeper region is more stable than in a shallower one. We also consider the distribution of kinetic and potential energy to clarify a feature characteristic of a large class of instabilities in shallow water flow. The instability of flows is caused by the decrease in the kinetic energy during the perturbation of waves. This phenomenon is known as negative energy modes and plays a vital role in applying the model to industrial equipment. A conclusion is that the equipartition of energies occurs if and only if the velocity difference is zero and the water depth is shallow enough to ignore the dispersive terms.}, language = {en} } @inproceedings{PedersenSchachlerHeideretal.2021, author = {Pedersen, Jaap and Schachler, Birgit and Heider, Anya and Pleßmann, Guido}, title = {Distribution System Planning with Battery Storage using Multiperiod Optimal Power Flow}, volume = {6}, booktitle = {14th International Renewable Energy Storage Conference 2020 (IRES 2020)}, doi = {https://doi.org/10.2991/ahe.k.210202.007}, pages = {41 -- 48}, year = {2021}, abstract = {The ongoing energy transition introduces new challenges for distribution networks and brings about the need to expand existing power grid capacities. In order to contain network expansion and with it economic costs, utilization of various flexibility options to reduce expansion needs is discussed. This paper proposes a multiperiod optimal power flow (MPOPF) approach with a new continuous network expansion formulation to optimize the deployment of flexibility options under the objective of minimizing network expansion costs. In a comparison of the newly proposed continuous network expansion formulation with an existing mixed integer formulation and a continuous interpretation of the latter the here proposed formulation is shown to be useful in order to obtain a solvable problem and contain computational efforts. The presented MPOPF including the flexibility options storage units and curtailment is then assessed on synthetic medium voltage grids and applied to evaluate the benefit of a combined vs. a stepwise optimization of these flexibility options. It is demonstrated that using a local solver the proposed approach is applicable and yields a solution in reasonable time. Furthermore, it is shown that the combined optimization generally leads to a more efficient utilization of the considered flexibility options and therefore lower grid expansion costs than the stepwise consideration.}, language = {en} } @article{AndersonTurnerKoch2022, author = {Anderson, Lovis and Turner, Mark and Koch, Thorsten}, title = {Generative deep learning for decision making in gas networks}, volume = {95}, journal = {Mathematical Methods of Operations Research}, publisher = {Springer Nature}, doi = {10.1007/s00186-022-00777-x}, pages = {503 -- 532}, year = {2022}, abstract = {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\%.}, language = {en} } @article{RehfeldtKoch2021, author = {Rehfeldt, Daniel and Koch, Thorsten}, title = {On the exact solution of prize-collecting Steiner tree problems}, journal = {INFORMS Journal on Computing}, doi = {10.1287/ijoc.2021.1087}, year = {2021}, language = {en} } @article{HenningsAndersonHoppmannBaumetal.2021, author = {Hennings, Felix and Anderson, Lovis and Hoppmann-Baum, Kai and Turner, Mark and Koch, Thorsten}, title = {Controlling transient gas flow in real-world pipeline intersection areas}, volume = {22}, journal = {Optimization and Engineering}, edition = {2}, publisher = {Springer Nature}, doi = {https://doi.org/10.1007/s11081-020-09559-y}, pages = {687 -- 734}, year = {2021}, abstract = {Compressor stations are the heart of every high-pressure gas transport network. Located at intersection areas of the network they are contained in huge complex plants, where they are in combination with valves and regulators responsible for routing and pushing the gas through the network. Due to their complexity and lack of data compressor stations are usually dealt with in the scientific literature in a highly simplified and idealized manner. As part of an ongoing project with one of Germany's largest Transmission System Operators to develop a decision support system for their dispatching center, we investigated how to automatize control of compressor stations. Each station has to be in a particular configuration, leading in combination with the other nearby elements to a discrete set of up to 2000 possible feasible operation modes in the intersection area. Since the desired performance of the station changes over time, the configuration of the station has to adapt. Our goal is to minimize the necessary changes in the overall operation modes and related elements over time, while fulfilling a preset performance envelope or demand scenario. This article describes the chosen model and the implemented mixed integer programming based algorithms to tackle this challenge. By presenting extensive computational results on real world data we demonstrate the performance of our approach.}, language = {en} } @article{RoessigPetkovic2020, author = {R{\"o}ssig, Ansgar and Petkovic, Milena}, title = {Advances in Verification of ReLU Neural Networks}, journal = {Journal of Global Optimization}, publisher = {Springer}, doi = {10.1007/s10898-020-00949-1}, year = {2020}, abstract = {We consider the problem of verifying linear properties of neural networks. Despite their success in many classification and prediction tasks, neural networks may return unexpected results for certain inputs. This is highly problematic with respect to the application of neural networks for safety-critical tasks, e.g. in autonomous driving. We provide an overview of algorithmic approaches that aim to provide formal guarantees on the behavior of neural networks. Moreover, we present new theoretical results with respect to the approximation of ReLU neural networks. On the other hand, we implement a solver for verification of ReLU neural networks which combines mixed integer programming (MIP) with specialized branching and approximation techniques. To evaluate its performance, we conduct an extensive computational study. For that we use test instances based on the ACAS Xu System and the MNIST handwritten digit data set. Our solver is publicly available and able to solve the verification problem for instances which do not have independent bounds for each input neuron.}, language = {en} } @inproceedings{RiedmuellerRivettaZittel2025, author = {Riedm{\"u}ller, Stephanie and Rivetta, Fabian and Zittel, Janina}, title = {Long-Term Multi-Objective Optimization for Integrated Unit Commitment and Investment Planning for District Heating Networks}, booktitle = {Operations Research Proceedings 2024}, publisher = {Springer Cham}, arxiv = {http://arxiv.org/abs/2410.06673}, doi = {10.1007/978-3-031-92575-7_33}, pages = {235 -- 241}, year = {2025}, abstract = {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 reasonable trade-offs between economic viability and environmental goals became necessary. We introduce a network-flow-based model class integrating unit commitment and long-term investment planning for multi-energy systems. While the integration of unit commitment and investment planning has been applied to multi-energy systems, a formal introduction and suitability for the application of long-term portfolio planning of an energy provider on an urban scale has yet to be met. Based on mixed integer linear programming, the model bridges the gap between overly detailed industrial modeling tools not designed for computational efficiency at scale and rather abstract academic models. The formulation is tested on Berlin's district heating network. Hence, the challenge lies in a large number of variables and constraints and the coupling of time steps, for example, through investment decisions. A case study explores different solutions on the Pareto front defined by optimal trade-offs between minimizing costs and CO2 emissions through a lexicographic optimization approach. The resulting solution catalog can provide decision-makers valuable insights into feasible transformation pathways, highlighting distinctions between robust and target-dependent investments.}, language = {en} } @inproceedings{PetkovicZittel2025, author = {Petkovic, Milena and Zittel, Janina}, title = {Resilient Forecasting of High-Dimensional Network Time Series in the Energy Domain: A Hybrid Approach}, booktitle = {Operations Research Proceedings 2023. OR 2023}, publisher = {Springer}, doi = {10.1007/978-3-031-58405-3_48}, pages = {375 -- 381}, year = {2025}, abstract = {Energy systems are complex networks consisting of various interconnected components. Accurate energy demand and supply forecasts are crucial for efficient system operation and decision-making. However, high-dimensional data, complex network structures, and dynamic changes and disruptions in energy networks pose significant challenges for forecasting models. To address this, we propose a hybrid approach for resilient forecasting of network time series (HRF-NTS) in the energy domain. Our approach combines mathematical optimization methods with state-of-the-art machine learning techniques to achieve accurate and robust forecasts for high-dimensional energy network time series. We incorporate an optimization framework to account for uncertainties and disruptive changes in the energy system. The effectiveness of the proposed approach is demonstrated through a case study of forecasting energy demand and supply in a complex, large-scale natural gas transmission network. The results show that the hybrid approach outperforms alternative prediction models in terms of accuracy and resilience to structural changes and disruptions, providing stable, multi-step ahead forecasts for different short to mid-term forecasting horizons.}, language = {en} } @inproceedings{YuekselErguenKochZittel2025, author = {Yueksel-Erguen, Inci and Koch, Thorsten and Zittel, Janina}, title = {Consistent flow scenario generation based on open data for operational analysis of European gas transport networks}, booktitle = {Operations Research Proceedings 2023. OR 2023}, publisher = {Springer}, doi = {10.1007/978-3-031-58405-3_63}, pages = {493 -- 499}, year = {2025}, abstract = {In recent years, European gas transport has been affected by major disruptive events like political issues such as, most recently, the Russian war on Ukraine. To incorporate the impacts of such events into decision-making during the energy transition, more complex models for gas network analysis are required. However, the limited availability of consistent data presents a significant obstacle in this endeavor. We use a mathematical-modeling-based scenario generator to deal with this obstacle. The scenario generator consists of capacitated network flow models representing the gas network at different aggregation levels. In this study, we present the coarse-to-fine approach utilized in this scenario generator.}, language = {en} } @inproceedings{YuekselErguenLitzelPeng2025, author = {Yueksel Erguen, Inci and Litzel, Ida and Peng, Hanqiu}, title = {Integrating Large Citation Datasets}, booktitle = {Operations Research Proceedings 2024. OR 2024}, doi = {10.1007/978-3-031-92575-7_7}, pages = {46 -- 52}, year = {2025}, abstract = {This paper explores methods for building a comprehensive citation graph using big data techniques to evaluate scientific impact more accurately. Traditional citation metrics have limitations, and this work investigates merging large citation datasets to create a more accurate picture. Challenges of big data, like inconsistent data formats and lack of unique identifiers, are addressed through deduplication efforts, resulting in a streamlined and reliable merged dataset with over 119 million records and 1.4 billion citations. We demonstrate that merging large citation datasets builds a more accurate citation graph facilitating a more robust evaluation of scientific impact.}, language = {en} } @article{ZakiyevaPetkovic2025, author = {Zakiyeva, Nazgul and Petkovic, Milena}, title = {High-dimensional high-frequency time series prediction with a mixed integer optimisation method}, journal = {Operations Research Proceedings 2023. OR 2023}, issn = {1438-0064}, doi = {10.1007/978-3-031-58405-3_54}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-93068}, pages = {423 -- 429}, year = {2025}, abstract = {We study a functional autoregressive model for high-frequency time series. We approach the estimation of the proposed model using a Mixed Integer Optimisation method. The proposed model captures serial dependence in the functional time series by including high-dimensional curves. We illustrate our methodology on large-scale natural gas network data. Our model provides more accurate day-ahead hourly out-of-sample forecast of the gas in and out-flows compared to alternative prediction models.}, language = {en} } @phdthesis{Rehfeldt2021, author = {Rehfeldt, Daniel}, title = {Faster algorithms for Steiner tree and related problems: From theory to practice}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-85148}, year = {2021}, language = {en} } @misc{HenningsPetkovicStreubel2021, author = {Hennings, Felix and Petkovic, Milena and Streubel, Tom}, title = {On the Numerical Treatment of Interlaced Target Values - Modeling, Optimization and Simulation of Regulating Valves in Gas Networks}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-85359}, year = {2021}, abstract = {Due to the current and foreseeable shifts in energy production, 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 full 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 commercial simulation tool SIMONE.}, language = {en} } @article{AignerClarnerLiersetal.2021, author = {Aigner, Kevin-Martin and Clarner, Jan-Patrick and Liers, Frauke and Martin, Alexander}, title = {Robust Approximation of Chance Constrained DC Optimal Power Flow under Decision-Dependent Uncertainty}, journal = {European Journal of Operational Research}, year = {2021}, abstract = {We propose a mathematical optimization model and its solution for joint chance constrained DC Optimal Power Flow. In this application, it is particularly important that there is a high probability of transmission limits being satisfied, even in the case of uncertain or fluctuating feed-in from renewable energy sources. In critical network situations where the network risks overload, renewable energy feed-in has to be curtailed by the transmission system operator (TSO). The TSO can reduce the feed-in in discrete steps at each network node. The proposed optimization model minimizes curtailment while ensuring that there is a high probability of transmission limits being maintained. The latter is modeled via (joint) chance constraints that are computationally challenging. Thus, we propose a solution approach based on the robust safe approximation of these constraints. Hereby, probabilistic constraints are replaced by robust constraints with suitably defined uncertainty sets constructed from historical data. The ability to discretely control the power feed-in then leads to a robust optimization problem with decision-dependent uncertainties, i.e. the uncertainty sets depend on decision variables. We propose an equivalent mixed-integer linear reformulation for box uncertainties with the exact linearization of bilinear terms. Finally, we present numerical results for different test cases from the Nesta archive, as well as for a real network. We consider the discrete curtailment of solar feed-in, for which we use real-world weather and network data. The experimental tests demonstrate the effectiveness of this method and run times are very fast. Moreover, on average the calculated robust solutions only lead to a small increase in curtailment, when compared to nominal solutions.}, language = {en} } @inproceedings{TateiwaShinanoYamamuraetal.2021, author = {Tateiwa, Nariaki and Shinano, Yuji and Yamamura, Keiichiro and Yoshida, Akihiro and Kaji, Shizuo and Yasuda, Masaya and Fujisawa, Katsuki}, title = {CMAP-LAP: Configurable Massively Parallel Solver for Lattice Problems}, booktitle = {HiPC 2021 proceedings}, year = {2021}, abstract = {Lattice problems are a class of optimization problems that are notably hard. There are no classical or quantum algorithms known to solve these problems efficiently. Their hardness has made lattices a major cryptographic primitive for post-quantum cryptography. Several different approaches have been used for lattice problems with different computational profiles; some suffer from super-exponential time, and others require exponential space. This motivated us to develop a novel lattice problem solver, CMAP-LAP, based on the clever coordination of different algorithms that run massively in parallel. With our flexible framework, heterogeneous modules run asynchronously in parallel on a large-scale distributed system while exchanging information, which drastically boosts the overall performance. We also implement full checkpoint-and-restart functionality, which is vital to high-dimensional lattice problems. Through numerical experiments with up to 103,680 cores, we evaluated the performance and stability of our system and demonstrated its high capability for future massive-scale experiments.}, language = {en} } @article{XuChenZhangetal.2021, author = {Xu, Xiaofei and Chen, Ying and Zhang, Ge and Koch, Thorsten}, title = {Modeling functional time series and mixed-type predictors with partially functional autoregressions*}, journal = {Journal of Business and Economic Statistics}, doi = {10.1080/07350015.2021.2011299}, pages = {1 -- 43}, year = {2021}, abstract = {In many business and economics studies, researchers have sought to measure the dynamic dependence of curves with high-dimensional mixed-type predictors. We propose a partially functional autoregressive model (pFAR) where the serial dependence of curves is controlled by coefficient operators that are defined on a two-dimensional surface, and the individual and group effects of mixed-type predictors are estimated with a two-layer regularization. We develop an efficient estimation with the proven asymptotic properties of consistency and sparsity. We show how to choose the sieve and tuning parameters in regularization based on a forward-looking criterion. In addition to the asymptotic properties, numerical validation suggests that the dependence structure is accurately detected. The implementation of the pFAR within a real-world analysis of dependence in German daily natural gas flow curves, with seven lagged curves and 85 scalar predictors, produces superior forecast accuracy and an insightful understanding of the dynamics of natural gas supply and demand for the municipal, industry, and border nodes, respectively.}, language = {en} } @article{RehfeldtFranzKoch2022, author = {Rehfeldt, Daniel and Franz, Henriette and Koch, Thorsten}, title = {Optimal Connected Subgraphs: Integer Programming Formulations and Polyhedra}, volume = {80}, journal = {Networks}, number = {3}, publisher = {Wiley}, doi = {10.1002/net.22101}, pages = {314 -- 332}, year = {2022}, language = {en} } @phdthesis{Lenz2021, author = {Lenz, Ralf}, title = {Optimization of Stationary Expansion Planning and Transient Network Control by Mixed-Integer Nonlinear Programming}, doi = {10.14279/depositonce-12765}, year = {2021}, language = {en} } @article{VuLitzelKoch2026, author = {Vu, Thi Huong and Litzel, Ida and Koch, Thorsten}, title = {Similarity-based fuzzy clustering scientific articles: potentials and challenges from mathematical and computational perspectives}, volume = {10}, journal = {Journal of Nonlinear and Variational Analysis}, number = {2}, publisher = {Biemdas}, arxiv = {http://arxiv.org/abs/2506.04045}, doi = {https://doi.org/10.23952/jnva.10.2026.2.8}, pages = {381 -- 401}, year = {2026}, abstract = {Fuzzy clustering, which allows an article to belong to multiple clusters with soft membership degrees, plays a vital role in analyzing publication data. This problem can be formulated as a constrained optimization model, where the goal is to minimize the discrepancy between the similarity observed from data and the similarity derived from a predicted distribution. While this approach benefits from leveraging state-of-the-art optimization algorithms, tailoring them to work with real, massive databases like OpenAlex or Web of Science - containing about 70 million articles and a billion citations - poses significant challenges. We analyze potentials and challenges of the approach from both mathematical and computational perspectives. Among other things, second-order optimality conditions are established, providing new theoretical insights, and practical solution methods are proposed by exploiting the structure of the problem. Specifically, we accelerate the gradient projection method using GPU-based parallel computing to efficiently handle large-scale data.}, language = {en} } @article{WakayamaYokoyamaShinanoetal.2018, author = {Wakayama, Yuki and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用の階層的関係を考慮した最適化(時間集約によるモデル縮約とその効果)}, journal = {エネルギー・資源学会第34回エネルギーシステム・経済・環境コンファレンス講演論文集}, pages = {401 -- 404}, year = {2018}, abstract = {A hierarchical mixed-integer linear programming method to solve optimal design problems of energy supply systems efficiently has been proposed. The original problem is solved by dividing it into a relaxed optimal design problem at the upper level and optimal operation problems which are independent of each other at the lower level. In this paper, a method of reducing model by time aggregation is proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. This method is realized only by clustering periods and averaging energy demands for clustered periods, while it guarantees to derive the optimal solution. On one hand, the method may decrease the number of design variables and costraints at the upper level, and thus the computation time at the upper level. On the other hand, it may increase the numbers of generated design solution candidates and solved optimal operation problems, and thus the computation time at both the levels. Though a case study on the optimal design of a cogeneration system, it is clarified how the model reduction is effective to enhance the computation efficiency.}, language = {ja} } @article{TaniguchiYokoyamaShinanoetal.2015, author = {Taniguchi, Shusuke and Yokoyama, Ryohei and Shinano, Yuji and Ohkura, Masashi and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用の階層的関係を考慮した最適化(多目的最適化におけるK-ベスト解の探索)}, journal = {エネルギー・資源学会第31回エネルギーシステム・経済・環境コンファレンス講演論文集}, pages = {267 -- 272}, year = {2015}, abstract = {A mixed-integer linear programming method utilizing the hierarchical relationship between design and operation variables proposed to solve the optimal design problem of energy supply systems efficiently is extended to search K-best solutions in multiobjective optimization: At the upper level, the optimal values of design variables are searched by the branch and bound method with operation variables relaxed to continuous ones; At the lower level, the values of operation variables are optimized independently at the respective periods set for variations in energy demands by the branch and bound method with the values of design variables given tentatively during the search at the upper level. A weighting method is employed for multiobjective optimization, and a weighted sum of the annual total cost and primary energy consumption is adopted as the objective function to be minimized. A practical case study on the optimal design of a cogeneration system is conducted. The validity and effectiveness of the proposed method are clarified, and the trade-off relationship between the annual total cost and primary energy consumption is confirmed.}, language = {ja} } @article{TakeuchiYokoyamaShinanoetal.2019, author = {Takeuchi, Kotaro and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {エネルギー供給システムの 設計と運用の階層的関係を考慮した最適化 (運用を考慮した期間クラスタリングによるモデル縮約)}, journal = {エネルギー・資源学会第35回エネルギーシステム・経済・環境コンファレンス講演論文集}, pages = {169 -- 174}, year = {2019}, abstract = {To attain the highest performance of energy supply systems, it is necessary to determine design specifications optimally in consideration of operational strategies corresponding to seasonal and hourly variations in energy demands. Mixed-integer linear programming (MILP) methods have been applied widely to such multi-period optimal design problems. A hierarchical MILP method has been proposed to solve the problems very efficiently. In addition, by utilizing features of the hierarchical MILP method, a method of reducing model by clustering periods has also been proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, by utilizing features of the hierarchical MILP method, a method of clustering periods is proposed based on the optimal operational strategies of energy supply systems obtained by solving the relaxed optimal design problem. As a case study, the method is applied to the optimal design of a gas turbine cogeneration system, and it is clarified that the method is effective to enhance the computation efficiency in comparison with a conventional method of clustering periods regularly.}, language = {ja} } @article{KamadaYokoyamaShinanoetal.2019, author = {Kamada, Hiroki and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {混合整数線形モデルによる エネルギー供給システムのロバスト最適設計 (階層的最適化手法の適用)}, journal = {エネルギー・資源学会第35回エネルギーシステム・経済・環境コンファレンス講演論文集}, pages = {163 -- 168}, year = {2019}, abstract = {A robust optimal design method of energy supply systems under uncertain energy demands has been proposed using a mixed- integer linear model for constituent equipment. A robust optimal design problem has been formulated as a three-level min-max- min optimization one by expressing uncertain energy demands by intervals, evaluating the robustness in a performance criterion based on the minimax regret criterion, and considering hierarchical relationships among design variables, uncertain energy demands, and operation variables. However, this method takes a long computation time, and thus it can be applied only to small-scale problems. In this paper, mixed-integer linear programming method in consideration of the hierarchical relationship between design and operation variables is applied to parts of the robust optimal design method which take long computation times to solve problems efficiently. In a case study, this revised method is applied to the robust optimal design of a cogeneration system with a simple configuration, and the validity and effectiveness of the method are ascertained.}, language = {ja} } @article{YokoyamaShinanoTaniguchietal.2014, author = {Yokoyama, Ryohei and Shinano, Yuji and Taniguchi, Syusuke and Ohkura, Masashi and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用の階層的関係を考慮した最適化(手法の提案)}, journal = {第33回エネルギー・資源学会研究発表会講演論文要旨集・講演論文集}, pages = {183 -- 188}, year = {2014}, abstract = {A mixed-integer linear programming (MILP) method utilizing the hierarchical relationship between design and op- eration variables is proposed to solve the optimal design problem of energy supply systems efficiently: At the upper level, the optimal values of design variables are searched by the branch and bound method; At the lower level, the values of operation variables are optimized by the branch and bound method under the values of design variables given tentatively during the search at the upper level; Lower bounds for the optimal value of the objective function are evaluated, and are utilized for the bounding operations at both the levels. This method is implemented into open and commercial MILP solvers. Illustrative and practical case studies on the optimal design of cogeneration systems are conducted, and the validity and effectiveness of the proposed method are clarified.}, language = {ja} } @article{PedersenSpreckelsenGotzesetal.2023, author = {Pedersen, Jaap and Spreckelsen, Klaus and Gotzes, Uwe and Zittel, Janina and Koch, Thorsten}, title = {Beimischung von Wasserstoff zum Erdgas: Eine Kapazit{\"a}tsstudie des deutschen Gasnetzes}, journal = {3R - Fachzeitschrift f{\"u}r Rohrleitungssystem}, number = {06/2023}, pages = {70 -- 75}, year = {2023}, abstract = {Die europ{\"a}ische Gasinfrastruktur wird disruptiv in ein zuk{\"u}nftiges dekarbonisiertes Energiesystem ver{\"a}ndert; ein Prozess, der angesichts der j{\"u}ngsten politischen Situation beschleunigt werden muss. Mit einem wachsenden Wasserstoffmarkt wird der pipelinebasierte Transport unter Nutzung der bestehenden Erdgasinfrastruktur wirtschaftlich sinnvoll, tr{\"a}gt zur Erh{\"o}hung der {\"o}ffentlichen Akzeptanz bei und beschleunigt den Umstellungsprozess. In diesem Fachbeitrag wird die maximal technisch machbare Einspeisung von Wasserstoff in das bestehende deutsche Erdgastransportnetz hinsichtlich regulatorischer Grenzwerte der Gasqualit{\"a}t analysiert. Die Analyse erfolgt auf Basis eines transienten Tracking-Modells, das auf dem allgemeinen Pooling-Problem einschließlich Linepack aufbaut. Es zeigt sich, dass das Gasnetz auch bei strengen Grenzwerten gen{\"u}gend Kapazit{\"a}t bietet, um f{\"u}r einen großen Teil der bis 2030 geplanten Erzeugungskapazit{\"a}t f{\"u}r gr{\"u}nen Wasserstoff als garantierter Abnehmer zu dienen.}, language = {de} } @article{YokoyamaShinanoTaniguchietal.2014, author = {Yokoyama, Ryohei and Shinano, Yuji and Taniguchi, Syusuke and Ohkura, Masashi and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用階層的関係を考慮した最適化(K-ベスト解の探索)}, journal = {日本機械学会第11回最適化シンポジウム2014講演論文集}, pages = {1 -- 4}, year = {2014}, abstract = {A mixed-integer linear programming methodutilizing the hierarchical relationship between design and operation variables proposed ot solve the optimal design problem of energy supply systems efficiently is extended ot search K-best solutions: At the upper level, the optimal values ofdesign variables are searched with operation variables relaxed to continuous ones; At the lower level, the values of operation variables are optimized with the values of design variables given tentatively; The obtained solution is used to renew K-best incumbent solutions, and the upper bound for the value of the objective function for K-best solutions is replaced correspondingly. A practical case study is conducted, and the validity and effectiveness of the proposed method are clarified.}, language = {ja} } @article{WakayamaYokoyamaShinanoetal.2018, author = {Wakayama, Yuki and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {階層的最適化によるエネルギ ー供給システムの最適設計・運用 (期間のクラスタリングに よるモデル縮約とその効果)}, journal = {日本機械学会関西支部第93期定時総会講演会講演論文集}, pages = {259 -- 260}, year = {2018}, abstract = {Ahierarchical mixed-integer linear programmingmethod has been proposed to solve optimal design problems of energy supply systems efficiently. In this paper, a method of reducing model by clustering periods is proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. This method is realized only by clustering periods and averaging energy demands for clustered periods, while it guarantees to derive the optimal solution. Through acase study on the optimaldesign of a cogeneration system, ti is clarified how the model reduction si effective ot enhance the computation efficiency.}, language = {ja} } @article{YokoyamaShinanoTakeuchietal.2019, author = {Yokoyama, Ryohei and Shinano, Yuji and Takeuchi, Kotaro and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用の 階層的関係を考慮した最適化 (モデル縮約のための期間クラスタリング手法の比較)}, journal = {第38回エネルギー・資源学会研究発表会講演論文集}, pages = {109 -- 114}, year = {2019}, abstract = {Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. As one of the strategies, a method of reducing model by time aggregation has been proposed to search design candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, three clustering methods are applied to time aggregation and compared with one another in terms of the computation efficiency. Especially, the k-medoids method is applied newly in addition to the time-series and operation-based methods applied previously. A case study is conducted on the optimal design of a gas turbine cogeneration system for district energy supply. Through the study, it turns out the k-medoids method is effective to shorten the computation time as compared with the time-series method, although it is necessary to set the number of clusters artifically in both the methods. It also turns out that the operation-based method is more effective than the k-medoids method in terms of the computation efficiency even with the number of clusters set automatically.}, language = {ja} } @article{TakeuchiYokoyamaShinanoetal.2020, author = {Takeuchi, Kotaro and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {エネルギー供給システムの 設計および運用の階層的関係を考慮した最適化 (多目的最適設計へのモデル縮約の適用)}, journal = {エネルギー・資源学会第36回エネルギーシステム・経済・環境コンファレンス講演論文集}, pages = {724 -- 729}, year = {2020}, abstract = {To attain the highest performance of energy supply systems, it is necessary to determine design specifications optimally in consideration of operational strategies corresponding to seasonal and hourly variations in energy demands. Mixed-integer linear programming (MILP) methods have been applied widely to such optimal design problems. A hierarchical MILP method has been proposed to solve the problems very efficiently. In addition, by utilizing features of the hierarchical MILP method, a method of reducing model by clustering periods based on the optimal operational strategies of equipment has been proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, these methods are applied to the multiobjective optimal design of a cogeneration system by considering the annual total cost and primary energy consumption as the objective functions to be minimized. Through a case study, it turns out that the model reduction by the operation-based time-period clustering is effective in terms of the computation efficiency when importance is given to the first objective function, while it is not when importance is given to the second objective function.}, language = {ja} } @article{YokoyamaShinanoWakui2021, author = {Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用の 階層的関係を考慮した最適化 (蓄エネルギー機器を有するシステムへの適用)}, journal = {第40回エネルギー・資源学会研究発表会講演論文集}, pages = {398 -- 403}, year = {2021}, abstract = {Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. As one of the strategies, a method of reducing model by time aggregation has been proposed to search design candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, the hierarchical MILP method with the strategies has been extendedly applied to the optimal design of energy supply systems with storage units. Especially, the method of re- ducing model is extended by aggregating representative days and sampling times differently in consideration of the characteristics of storage units. A case study is conducted on the optimal design of a gas turbine cogeneration system with a thermal storage unit for district energy supply. Through the study, it turns out the hierarchical MILP method is effective to derive the optimal solution as compared with a conventional method. It also turns out that the model reduction with the special time aggregation is effective to shorten the computation time as compared with that without time aggregation in case that the number of candidates for equipment capacities is relatively small.}, language = {ja} } @article{YokoyamaShinanoWakui2022, author = {Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {時間集約によるエネルギー供給システムの 近似最適設計解の導出および評価 (階層的最適化を援用した設計解の評価)}, journal = {エネルギー・資源学会第38回エネルギーシステム・経済・環境コンファレンス講演論文集}, pages = {468 -- 473}, year = {2022}, abstract = {For the purpose of attaining the highest performance of energy supply systems, it is important to design the systems optimally in consideration of their operational strategies for seasonal and hourly variations in energy demands. An ap- proach to solve such an optimal design problem with a large number of periods efficiently is to derive an approximate optimal design solution by aggregating periods with a clustering method. However, such an approach does not provide any information on the accuracy for the optimal value of the objective function. The purpose of this paper is to provide a time aggregation method for deriving aprroximate optimal design solutions and evaluting their values of the objective function. Especially, a method of evaluating design solutions is presented here using both methods of evaluating the robustness under uncertain energy demands and solving optimal design problems by a hierarchical approach. A case study is conducted for a cogeneration system with a practical configuration, and it turns out that the proposed approach enables one to evaluate effective lower bounds for the optimal value of the objective function as compared with those obtained by a conventional approach.}, language = {ja} } @article{YokoyamaShinanoWakui2022, author = {Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {時間集約によるエネルギー供給システムの 近似最適設計解の導出および評価 (階層的最適化を援用した近似最適設計)}, journal = {第41回エネルギー・資源学会研究発表会講演論文集}, pages = {144 -- 148}, year = {2022}, abstract = {For the purpose of attaining the highest performance of energy supply systems, it is important to design the systems optimally in consideration of their operational strategies for seasonal and hourly variations in energy demands. An ap- proach to efficiently solve such an optimal design problem with a large number of periods for variations in energy de- mands is to derive an approximate optimal design solution by aggregating periods with a clustering method. However, such an approach does not provide any information on the accuracy for the optimal value of the objective function. The purpose of this paper is to propose a time aggregation approach for deriving suitable aprroximate optimal design solutions and evaluting their values of the objective function accurately. This time aggregation approach is realized by combining a robust optimal design method under uncertain energy demands and a hierarchical approach for solving large scale optimal design problems. A case study is conducted for a cogeneration system with a practical configuration, and it turns out that the proposed approach enables one to evaluate effective upper and lower bounds for the optimal value of the objective function as compared with those obtained by a conventional approach.}, language = {ja} } @article{YokoyamaShinanoWakayamaetal.2019, author = {Yokoyama, Ryohei and Shinano, Yuji and Wakayama, Yuki and Wakui, Tetsuya}, title = {Model reduction by time aggregation for optimal design of energy supply systems by an MILP hierarchical branch and bound method}, volume = {181}, journal = {Energy}, pages = {782 -- 792}, year = {2019}, abstract = {Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of en- ergy supply systems in consideration of multi-period operation. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. An original problem has been solved by dividing it into a relaxed optimal design problem at the upper level and optimal operation problems which are independent of one another at the lower level. In addition, some strategies have been pro- posed to enhance the computation efficiency furthermore. In this paper, a method of reducing model by time aggregation is proposed as a novel strategy to search design candidates efficiently in the relaxed optimal design problem at the upper level. In addition, the previous strategies are modified in accor- dance with the novel strategy. This method is realized only by clustering periods and averaging energy demands for clustered periods, while it guarantees to derive the optimal solution. Thus, it may decrease the computation time at the upper level. Through a case study on the optimal design of a gas turbine cogeneration system, it is clarified how the model reduction is effective to enhance the computation efficiency in comparison and combination with the modified previous strategies.}, language = {en} } @article{KamadaYokoyamaShinanoetal.2020, author = {Kamada, Hiroki and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {階層的最適化手法の援用による エネルギー供給システムのロバスト最適設計}, journal = {エネルギー・資源学会第36回エネルギーシステム・経済・環境コンファレンス講演論文集}, pages = {730 -- 735}, year = {2020}, abstract = {A robust optimal design method of energy supply systems under uncertain energy demands has been proposed using a mixed- integer linear model for constituent equipment. A robust optimal design problem has been formulated as a three-level min-max- min optimization one by expressing uncertain energy demands by intervals, evaluating the robustness in a performance criterion based on the minimax regret criterion, and considering hierarchical relationships among design variables, uncertain energy demands, and operation variables. Since this problem must be solved by a special algorithm and is too difficult to solve even using a commercial solver, a hierarchical optimization approach has been applied to solve the problem but its application is limited only to small scale toy problems. In this paper, some strategies are introduced into the hierarchical optimization approach to enhance the computation efficiency for the purpose of applying the approach to large scale practical problems. In a case study, the proposed approach is applied to the robust optimal design of a cogeneration system with a complex configuration, and the validity and effectiveness of the method are ascertained.}, language = {ja} } @article{TakeuchiYokoyamaShinanoetal.2020, author = {Takeuchi, Kotaro and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {エネルギー供給システムの設計および運用の階層的関係を考慮した最適化 (k-メドイド法に基づく期間クラスタリングの適用)}, journal = {日本機械学会関西支部第95期定時総会講演会講演論文集}, pages = {1 -- 4}, year = {2020}, abstract = {To attain the highest performance of energy supply systems, it is necessary to determine design specifications optimally in consideration of operational strategies corresponding to seasonal and hourly variations in energy demands. A hierarchical mixed-integer linear programming method has been proposed to solve such an optimal design problem efficiently. In this paper, a method of reducing model by clustering periods with the k-medoids method is applied to the relaxed optimal design problem at the upper level. Through a case study, it is clarified how the proposed method is effective to enhance the computation efficiency in a large scale optimal design problem.}, language = {ja} } @article{KamadaYokoyamaShinanoetal.2020, author = {Kamada, Hiroki and Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {階層的最適化手法を用いた エネルギー供給システムのロバスト性評価}, journal = {日本機械学会関西支部第95期定時総会講演会講演論文集}, pages = {1 -- 4}, year = {2020}, abstract = {A robust optimal design method of energy supply systems under uncertain energy demands has been proposed using a mixed-integer linear model for constituent equipment. However, this method takes a long computation time, and thus it can be applied only to small-scale problems. In this paper, a hierarchical optimization method is applied to two types of optimization problems for evaluating robustness to solve them efficiently. In a case study, the proposed method is applied to a cogeneration system with a complex configuration, and the validity and effectiveness of the method are ascertained.}, language = {ja} } @article{PedersenSpreckelsenGotzesetal.2023, author = {Pedersen, Jaap and Spreckelsen, Klaus and Gotzes, Uwe and Zittel, Janina and Koch, Thorsten}, title = {Beimischung von Wasserstoff zum Erdgas: Eine Kapazit{\"a}tsstudie des deutschen Gasnetzes}, journal = {gwf Gas + Energie}, edition = {06/2023}, publisher = {Vulkan Verlag}, year = {2023}, abstract = {Die europaische Gasinfrastruktur wird disruptiv in ein zukunftiges dekarbonisiertes Energiesystem ver{\"a}ndert; ein Prozess, der angesichts der j{\"u}ngsten politischen Situation beschleunigt werden muss. Mit einem wachsenden Wasserstoffmarkt wird der pipelinebasierte Transport unter Nutzung der bestehenden Erdgasinfrastruktur wirtschaftlich sinnvoll, tr{\"a}gt zur Erh{\"o}hung der {\"o}ffentlichen Akzeptanz bei und beschleunigt den Umstellungsprozess. In diesem Beitrag wird die maximal technisch machbare Einspeisung von Wasserstoff in das bestehende deutsche Erdgastransportnetz hinsichtlich regulatorischer Grenzwerte der Gasqualit{\"a}t analysiert. Die Analyse erfolgt auf Basis eines transienten Tracking-Modells, das auf dem allgemeinen Pooling-Problem einschließlich Linepack aufbaut. Es zeigt sich, dass das Gasnetz auch bei strengen Grenzwerten gen ̈ugend Kapazit{\"a}t bietet, um f{\"u}r einen großen Teil der bis 2030 geplanten Erzeugungskapazit{\"a}t f{\"u}r gr{\"u}nen Wasserstoff als garantierter Abnehmer zu dienen.}, language = {de} } @article{YokoyamaShinanoWakui2019, author = {Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {Evaluation of Design Alternatives for a Gas Turbine Cogeneration Plant Based on Multiobjective K-Best Solutions}, journal = {International Conference on Power Engineering-2019}, pages = {1112 -- 1117}, year = {2019}, abstract = {To realize the best performance in energy supply, it is an important task to determine types, capacities, and numbers of energy conversion equipment appropriately. It is also necessary to take account of seasonal and hourly variations in energy demands and corresponding operational strategies of equipment. The mixed-integer linear programming (MILP) method has been utilized widely to derive the optimal solution for such a design problem. From the design viewpoint, it is important to generate not only the optimal solution but also suboptimal ones which follow the optimal one without omission, what are called K-best solutions. In this paper, an MILP method utilizing the hierarchical relationship between design and operation variables is applied along with some strategies to efficiently drive K-best solutions of a multiobjective optimal design problem of a gas turbine cogeneration system for district energy supply. The annual total cost and primary energy consumption are adopted as the objective functions to be minimized. A case study is conducted, and K-best solutions with an allowable increase in the value of the combined objective function are derived for each value of the weight for the annual total cost. Through the study, it is clarified how the weight affects the computation time, the number of the K-best solutions, and the design specifications and the values of the objective functions for the K-best solutions.}, language = {en} } @article{YokoyamaHiramatsuShinanoetal.2022, author = {Yokoyama, Ryohei and Hiramatsu, Yuto and Shinano, Yuji and Wakui, Tetsuya}, title = {Evaluation of robustness in multiple performance criteria for designing energy supply systems based on a mixed-integer linear model}, journal = {The 35th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2022)}, pages = {1937 -- 1948}, year = {2022}, abstract = {In designing energy supply systems, it is important to consider the uncertainty in energy demands, evaluate the robustness in some performance criteria, and heighten the robustness. A robust optimal design method has been previously proposed to maximize the robustness in a single performance criterion against the uncertainty in energy demands based on a mixed-integer linear model. In this paper, as a preliminary step toward multiobjective robust optimal design, a method of evaluating robustness in multiple performance criteria against the uncertainty in energy demands is proposed based on a mixed-integer linear model. The problems of evaluating the robustness in the performance criteria are formulated as bilevel mixed-integer linear programming (MILP) ones. They are solved by evaluating lower and upper bounds for the maximum regrets in the performance criteria alternately and repeatedly with the aid of a solution method based on reformulation and decomposition. In addition, for the purpose of applying the proposed method to practical problems, a hierarchical MILP method is used to efficiently solve some MILP problems in the solution process. Through a case study on a cogeneration system, the robustness in the annual total cost and primary energy consumption is evaluated and its trade-off relationship is clarified. As a result, it turns out how the values of these performance criteria are close to the optimal ones in relation to the uncertainty in energy demands. This work will be an important step toward developing a multiobjective robust optimal design method.}, language = {en} } @article{YokoyamaShinanoTaniguchietal.2019, author = {Yokoyama, Ryohei and Shinano, Yuji and Taniguchi, Syusuke and Wakui, Tetsuya}, title = {Search for K-best solutions in optimal design of energy supply systems by an extended MILP hierarchical branch and bound method}, volume = {184}, journal = {Energy}, doi = {https://doi.org/10.1016/j.energy.2018.02.077}, pages = {45 -- 57}, year = {2019}, abstract = {For the purpose of making a decision in the optimal design of an energy supply system, it is important to investigate not only the optimal solution but also suboptimal ones which follow the optimal one without any omissions, what are called K-best solutions. In this paper, a mixed-integer linear programming method utilizing the hierarchical relationship between design and operation variables proposed previ- ously is extended to search the K-best solutions very efficiently. In addition, methods for updating the incumbents are incorporated into the extended method for three options for the criterion set newly in deriving the K-best solutions. This extended method is implemented into open and commercial MILP solvers, and is applied to illustrative and practical case studies, respectively, on the optimal design of cogeneration systems. Through the studies, it turns out that the proposed method is much superior in terms of solution optimality and computation efficiency to a conventional method, and that the computation efficiency to derive one of the K-best solutions by the proposed method increases with the number of K-best solutions. In addition, features of the K-best solutions in the value of objective function are clarified.}, language = {en} } @article{YokoyamaHiramatsuShinanoetal.2022, author = {Yokoyama, Ryohei and Hiramatsu, Yuto and Shinano, Yuji and Wakui, Tetsuya}, title = {Evaluation of robustness in multiple performance criteria for designing energy supply systems based on a mixed-integer linear model}, journal = {Proceedings of the 35th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2022)}, pages = {1937 -- 1948}, year = {2022}, abstract = {In designing energy supply systems, it is important to consider the uncertainty in energy demands, evaluate the robustness in some performance criteria, and heighten the robustness. A robust optimal design method has been previously proposed to maximize the robustness in a single performance criterion against the uncertainty in energy demands based on a mixed-integer linear model. In this paper, as a preliminary step toward multiobjective robust optimal design, a method of evaluating robustness in multiple performance criteria against the uncertainty in energy demands is proposed based on a mixed-integer linear model. The problems of evaluating the robustness in the performance criteria are formulated as bilevel mixed-integer linear programming (MILP) ones. They are solved by evaluating lower and upper bounds for the maximum regrets in the performance criteria alternately and repeatedly with the aid of a solution method based on reformulation and decomposition. In addition, for the purpose of applying the proposed method to practical problems, a hierarchical MILP method is used to efficiently solve some MILP problems in the solution process. Through a case study on a cogeneration system, the robustness in the annual total cost and primary energy consumption is evaluated and its trade-off relationship is clarified.}, language = {en} } @article{YokoyamaShinanoTakeuchietal.2019, author = {Yokoyama, Ryohei and Shinano, Yuji and Takeuchi, Kotaro and Wakui, Tetsuya}, title = {Operation-based time-period clustering for optimal design of energy supply systems by a hierarchical MILP method}, journal = {THE 32ND INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS(ECOS 2019)}, pages = {527 -- 539}, year = {2019}, abstract = {Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. As one of the strategies, a method of reducing model by time aggregation has been proposed to search design candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, a method of clustering periods has been proposed based on the optimal operational strategies of the systems to avoid a large decrease in the lower bound for the optimal value of the objective function by model reduction. This method has been realized only by solving the relaxed optimal design problem at the upper level in advance. The method can decrease the number of operation variables and constraints at the upper level, and thus can decrease the computation time at the upper level. Through a case study on the optimal design of a gas turbine cogeneration system, it is clarified how the proposed clustering method is effective to enhance the computation efficiency in comparison with the conventional one which clusters periods regularly in time series.}, language = {en} } @article{RehfeldtKochShinano2023, author = {Rehfeldt, Daniel and Koch, Thorsten and Shinano, Yuji}, title = {Faster exact solution of sparse MaxCut and QUBO problems}, volume = {15}, journal = {Mathematical Programming Computation}, doi = {10.1007/s12532-023-00236-6}, pages = {445 -- 470}, year = {2023}, abstract = {The maximum-cut problem is one of the fundamental problems in combinatorial optimization. With the advent of quantum computers, both the maximum-cut and the equivalent quadratic unconstrained binary optimization problem have experienced much interest in recent years. This article aims to advance the state of the art in the exact solution of both problems—by using mathematical programming techniques. The main focus lies on sparse problem instances, although also dense ones can be solved. We enhance several algorithmic components such as reduction techniques and cutting-plane separation algorithms, and combine them in an exact branch-and-cut solver. Furthermore, we provide a parallel implementation. The new solver is shown to significantly outperform existing state-of-the-art software for sparse maximum-cut and quadratic unconstrained binary optimization instances. Furthermore, we improve the best known bounds for several instances from the 7th DIMACS Challenge and the QPLIB, and solve some of them (for the first time) to optimality.}, language = {en} } @article{LeKoch2023, author = {Le, Thi Thai and Koch, Thorsten}, title = {Effect of inertia force on the interface stability of a tangential-velocity discontinuity in porous media}, volume = {169}, journal = {International Journal of Multiphase Flow}, doi = {10.1016/j.ijmultiphaseflow.2023.104612}, year = {2023}, abstract = {The present study investigates the stability of a tangential-velocity discontinuity in porous media during the withdrawing and injecting processes of natural gases from and into an underground gas storage. The focus is placed on analyzing the impact of inertia forces on the interface stability using the Forchheimer equations. Other publications have relied primarily on Darcy's law to describe flow stability in porous media. However, Darcy's law only adequately describes flows in which viscous forces dominate over inertia forces. As the flow rate increases, the significance of inertia forces becomes more pronounced, and Darcy's law becomes insufficient for considering such flows. Our findings indicate that even a slight consideration of the inertia effect leads to permanent destabilization of the discontinuity interface, regardless of the fluid viscosity or the Mach number. In contrast, when the inertia effect is neglected, the interface is stabilized across the entire Mach number range if the fluid viscosity is strong enough.}, language = {en} } @article{YokoyamaShinanoWakui2022, author = {Yokoyama, Ryohei and Shinano, Yuji and Wakui, Tetsuya}, title = {Day and time aggregations for optimal design of energy supply systems with storage units by a hierarchical MILP method}, journal = {The 35th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2022)}, pages = {1891 -- 1902}, year = {2022}, abstract = {Mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. As one of the strategies, a method of reducing model by time aggregation has been proposed to search design candidates efficiently in the relaxed optimal design problem at the upper level. In this paper, the hierarchical MILP method with the strategies is extendedly applied to the optimal design of energy supply systems with storage units. Especially, the method of reducing model is extended by aggregating both representative days and sampling times separately in consideration of the characteristics of energy storage units. A case study is conducted on the optimal design of a cogeneration system with a thermal storage tank. Through the study, it turns out the hierarchical MILP method is effective to derive the optimal solutions in short computation times. It also turns out that the model reduction with day and time aggregations is effec- tive to shorten the computation times furthermore when the number of candidates for equipment capacities is relatively small.}, language = {en} } @article{ChenKochZakiyevaetal.2023, author = {Chen, Ying and Koch, Thorsten and Zakiyeva, Nazgul and Liu, Kailiang and Xu, Zhitong and Chen, Chun-houh and Nakano, Junji and Honda, Keisuke}, title = {Article's scientific prestige: Measuring the impact of individual articles in the web of science}, volume = {17}, journal = {Journal of Informetrics}, number = {1}, doi = {10.1016/j.joi.2023.101379}, pages = {101379}, year = {2023}, abstract = {We performed a citation analysis on the Web of Science publications consisting of more than 63 million articles and 1.45 billion citations on 254 subjects from 1981 to 2020. We proposed the Article's Scientific Prestige (ASP) metric and compared this metric to number of citations (\#Cit) and journal grade in measuring the scientific impact of individual articles in the large-scale hierarchical and multi-disciplined citation network. In contrast to \#Cit, ASP, that is computed based on the eigenvector centrality, considers both direct and indirect citations, and provides steady-state evaluation cross different disciplines. We found that ASP and \#Cit are not aligned for most articles, with a growing mismatch amongst the less cited articles. While both metrics are reliable for evaluating the prestige of articles such as Nobel Prize winning articles, ASP tends to provide more persuasive rankings than \#Cit when the articles are not highly cited. The journal grade, that is eventually determined by a few highly cited articles, is unable to properly reflect the scientific impact of individual articles. The number of references and coauthors are less relevant to scientific impact, but subjects do make a difference.}, language = {en} } @inproceedings{TurnerBertholdBesanconetal.2023, author = {Turner, Mark and Berthold, Timo and Besan{\c{c}}on, Mathieu and Koch, Thorsten}, title = {Cutting Plane Selection with Analytic Centers and Multiregression}, volume = {13884}, booktitle = {Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2023.}, publisher = {Springer}, doi = {10.1007/978-3-031-33271-5_4}, pages = {52 -- 68}, year = {2023}, abstract = {Cutting planes are a crucial component of state-of-the-art mixed-integer programming solvers, with the choice of which subset of cuts to add being vital for solver performance. We propose new distance-based measures to qualify the value of a cut by quantifying the extent to which it separates relevant parts of the relaxed feasible set. For this purpose, we use the analytic centers of the relaxation polytope or of its optimal face, as well as alternative optimal solutions of the linear programming relaxation. We assess the impact of the choice of distance measure on root node performance and throughout the whole branch-and-bound tree, comparing our measures against those prevalent in the literature. Finally, by a multi-output regression, we predict the relative performance of each measure, using static features readily available before the separation process. Our results indicate that analytic center-based methods help to significantly reduce the number of branch-and-bound nodes needed to explore the search space and that our multiregression approach can further improve on any individual method.}, language = {en} }