@article{ChenKochPengetal.2025, author = {Chen, Ying and Koch, Thorsten and Peng, Hanqui and Zhang, Hongrui}, title = {Benchmarking of Quantum and Classical Computing in Large-Scale Dynamic Portfolio Optimization Under Market Frictions}, arxiv = {http://arxiv.org/abs/2502.05226}, year = {2025}, abstract = {Quantum computing is poised to transform the financial industry, yet its advantages over traditional methods have not been evidenced. As this technology rapidly evolves, benchmarking is essential to fairly evaluate and compare different computational strategies. This study presents a challenging yet solvable problem of large-scale dynamic portfolio optimization under realistic market conditions with frictions. We frame this issue as a Quadratic Unconstrained Binary Optimization (QUBO) problem, compatible with digital computing and ready for quantum computing, to establish a reliable benchmark. By applying the latest solvers to real data, we release benchmarks that help verify true advancements in dynamic trading strategies, either quantum or digital computing, ensuring that reported improvements in portfolio optimization are based on robust, transparent, and comparable metrics.}, language = {en} } @article{PetkovicZittel2025, author = {Petkovic, Milena and Zittel, Janina}, title = {Leveraging Transfer Learning to Overcome Data Limitations in Czochralski Crystal Growth}, volume = {8}, journal = {Advanced Theory and Simulations}, number = {11}, doi = {10.1002/adts.202500677}, year = {2025}, language = {en} } @misc{TateiwaShinanoYasudaetal.2021, author = {Tateiwa, Nariaki and Shinano, Yuji and Yasuda, Masaya and Kaji, Shizuo and Yamamura, Keiichiro and Fujisawa, Katsuki}, title = {Massively parallel sharing lattice basis reduction}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-85209}, year = {2021}, abstract = {For cryptanalysis in lattice-based schemes, the performance evaluation of lattice basis reduction using high-performance computers is becoming increasingly important for the determination of the security level. We propose a distributed and asynchronous parallel reduction algorithm based on randomization and DeepBKZ, which is an improved variant of the block Korkine-Zolotarev (BKZ) reduction algorithm. Randomized copies of a lattice basis are distributed to up to 103,680 cores and independently reduced in parallel, while some basis vectors are shared asynchronously among all processes via MPI. There is a trade-off between randomization and information sharing; if a substantial amount of information is shared, all processes will work on the same problem, thereby diminishing the benefit of parallelization. To monitor this balance between randomness and sharing, we propose a metric to quantify the variety of lattice bases. We empirically find an optimal parameter of sharing for high-dimensional lattices. We demonstrate the efficacy of our proposed parallel algorithm and implementation with respect to both performance and scalability through our experiments.}, language = {en} } @misc{FujiiKimKojimaetal.2023, author = {Fujii, Koichi and Kim, Sunyoung and Kojima, Masakazu and Mittelmann, Hans D. and Shinano, Yuji}, title = {An Exceptionally Difficult Binary Quadratic Optimization Problem with Symmetry: a Challenge for The Largest Unsolved QAP Instance Tai256c}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-93072}, year = {2023}, abstract = {Tai256c is the largest unsolved quadratic assignment problem (QAP) instance in QAPLIB. It is known that QAP tai256c can be converted into a 256 dimensional binary quadratic optimization problem (BQOP) with a single cardinality constraint which requires the sum of the binary variables to be 92. As the BQOP is much simpler than the original QAP, the conversion increases the possibility to solve the QAP. Solving exactly the BQOP, however, is still very difficult. Indeed, a 1.48\% gap remains between the best known upper bound (UB) and lower bound (LB) of the unknown optimal value. This paper shows that the BQOP admits a nontrivial symmetry, a property that makes the BQOP very hard to solve. The symmetry induces equivalent subproblems in branch and bound (BB) methods. To effectively improve the LB, we propose an efficient BB method that incorporates a doubly nonnegative relaxation, the standard orbit branching and a technique to prune equivalent subproblems. With this BB method, a new LB with 1.25\% gap is successfully obtained, and computing an LB with 1.0\% gap is shown to be still quite difficult.}, language = {en} } @article{XuChenZhangetal.2022, 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}, volume = {42}, journal = {Journal of Business \& Economic Statistics}, number = {2}, publisher = {Informa UK Limited}, issn = {0735-0015}, doi = {https://doi.org/10.1080/07350015.2021.2011299}, pages = {349 -- 366}, year = {2022}, language = {en} } @inproceedings{HadjidimitriouLippiNastroetal.2024, author = {Hadjidimitriou, Natalia Selini and Lippi, Marco and Nastro, Raffaele and Koch, Thorsten and Mamei, Marco}, title = {Short-Term Forecasting of Energy Consumption and Production in Local Energy Communities}, booktitle = {2024 32nd International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)}, publisher = {IEEE}, doi = {10.1109/WETICE64632.2024.00022}, pages = {74 -- 79}, year = {2024}, language = {en} } @article{YokoyamaKamadaShinanoetal.2021, author = {Yokoyama, Ryohei and Kamada, Hiroki and Shinano, Yuji and Wakui, Tetsuya}, title = {A hierarchical optimization approach to robust design of energy supply systems based on a mixed-integer linear model}, volume = {229}, journal = {Energy}, doi = {https://doi.org/10.1016/j.energy.2021.120343}, year = {2021}, abstract = {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 hierarchical mixed-integer linear programming (MILP) method is proposed to maximize the robustness of energy supply 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 criterion, and considering relationships among integer design variables, uncertain energy demands, and integer 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. Different types of optimization problems are solved by applying a hierarchical MILP method developed for ordinary optimal design problems without and 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.}, language = {en} } @article{LenzBecker2022, author = {Lenz, Ralf and Becker, Kai-Helge}, title = {Optimization of Capacity Expansion in Potential-driven Networks including Multiple Looping - A comparison of modelling approaches}, volume = {44}, journal = {OR Spectrum}, doi = {https://doi.org/10.1007/s00291-021-00648-7}, pages = {179 -- 224}, year = {2022}, abstract = {In commodity transport networks such as natural gas, hydrogen and water networks, flows arise from nonlinear potential differences between the nodes, which can be represented by so-called "potential-driven" network models. When operators of these networks face increasing demand or the need to handle more diverse transport situations, they regularly seek to expand the capacity of their network by building new pipelines parallel to existing ones ("looping"). The paper introduces a new mixed-integer non-linear programming (MINLP) model and a new non-linear programming (NLP) model and compares these with existing models for the looping problem and related problems in the literature, both theoretically and experimentally. On this basis, we give recommendations about the circumstances under which a certain model should be used. In particular, it turns out that one of our novel models outperforms the existing models. Moreover, the paper is the first to include the practically relevant option that a particular pipeline may be looped several times.}, language = {en} } @article{RehfeldtKoch2023, author = {Rehfeldt, Daniel and Koch, Thorsten}, title = {Implications, Conflicts, and Reductions for Steiner Trees}, volume = {197}, journal = {Mathematical Programming}, publisher = {Springer}, doi = {10.1007/s10107-021-01757-5}, pages = {903 -- 966}, year = {2023}, language = {en} } @article{FujiiKimKojimaetal.2024, author = {Fujii, Koichi and Kim, Sunyoung and Kojima, Masakazu and Mittelmann, Hans D. and Shinano, Yuji}, title = {An exceptionally difficult binary quadratic optimization problem with symmetry: a challenge for the largest unsolved QAP instance Tai256c}, journal = {Optimization Letters}, publisher = {Springer Science and Business Media LLC}, issn = {1862-4472}, doi = {10.1007/s11590-024-02157-2}, year = {2024}, abstract = {Tai256c is the largest unsolved quadratic assignment problem (QAP) instance in QAPLIB. It is known that QAP tai256c can be converted into a 256 dimensional binary quadratic optimization problem (BQOP) with a single cardinality constraint which requires the sum of the binary variables to be 92. As the BQOP is much simpler than the original QAP, the conversion increases the possibility to solve the QAP. Solving exactly the BQOP, however, is still very difficult. Indeed, a 1.48\% gap remains between the best known upper bound (UB) and lower bound (LB) of the unknown optimal value. This paper shows that the BQOP admits a nontrivial symmetry, a property that makes the BQOP very hard to solve. Despite this difficulty, it is imperative to decrease the gap in order to ultimately solve the BQOP exactly. To effectively improve the LB, we propose an efficient BB method that incorporates a doubly nonnegative relaxation, the orbit branching and the isomorphism pruning. With this BB method, a new LB with 1.25\% gap is successfully obtained, and computing an LB with gap is shown to be still quite difficult.}, language = {en} }