TY - JOUR A1 - Bestuzheva, Ksenia A1 - Chmiela, Antonia A1 - Müller, Benjamin A1 - Serrano, Felipe A1 - Vigerske, Stefan A1 - Wegscheider, Fabian T1 - Global Optimization of Mixed-Integer Nonlinear Programs with SCIP 8.0 JF - Journal of Global Optimization N2 - For over ten years, the constraint integer programming framework SCIP has been extended by capabilities for the solution of convex and nonconvex mixed-integer nonlinear programs (MINLPs). With the recently published version 8.0, these capabilities have been largely reworked and extended. This paper discusses the motivations for recent changes and provides an overview of features that are particular to MINLP solving in SCIP. Further, difficulties in benchmarking global MINLP solvers are discussed and a comparison with several state-of-the-art global MINLP solvers is provided. Y1 - 2023 U6 - https://doi.org/10.1007/s10898-023-01345-1 ER - TY - JOUR A1 - Chmiela, Antonia A1 - Muñoz, Gonzalo A1 - Serrano, Felipe T1 - Monoidal strengthening and unique lifting in MIQCPs JF - Mathematical Programming B Y1 - 2025 U6 - https://doi.org/10.1007/s10107-024-02112-0 VL - 210 SP - 189 EP - 222 ER - TY - JOUR A1 - Chmiela, Antonia A1 - Muñoz, Gonzalo A1 - Serrano, Felipe T1 - On the implementation and strengthening of intersection cuts for QCQPs JF - Mathematical Programming B Y1 - 2023 U6 - https://doi.org/10.1007/s10107-022-01808-5 VL - 197 SP - 549 EP - 586 ER - TY - CHAP A1 - Chmiela, Antonia A1 - Khalil, Elias B. A1 - Gleixner, Ambros A1 - Lodi, Andrea A1 - Pokutta, Sebastian T1 - Learning to Schedule Heuristics in Branch and Bound T2 - Thirty-fifth Conference on Neural Information Processing Systems, NeurIPS 2021 N2 - Primal heuristics play a crucial role in exact solvers for Mixed Integer Programming (MIP). While solvers are guaranteed to find optimal solutions given sufficient time, real-world applications typically require finding good solutions early on in the search to enable fast decision-making. While much of MIP research focuses on designing effective heuristics, the question of how to manage multiple MIP heuristics in a solver has not received equal attention. Generally, solvers follow hard-coded rules derived from empirical testing on broad sets of instances. Since the performance of heuristics is instance-dependent, using these general rules for a particular problem might not yield the best performance. In this work, we propose the first data-driven framework for scheduling heuristics in an exact MIP solver. By learning from data describing the performance of primal heuristics, we obtain a problem-specific schedule of heuristics that collectively find many solutions at minimal cost. We provide a formal description of the problem and propose an efficient algorithm for computing such a schedule. Compared to the default settings of a state-of-the-art academic MIP solver, we are able to reduce the average primal integral by up to 49% on a class of challenging instances. Y1 - 2021 ER - TY - CHAP A1 - Chmiela, Antonia A1 - Gleixner, Ambros A1 - Lichocki, Pawel A1 - Pokutta, Sebastian T1 - Online Learning for Scheduling MIP Heuristics T2 - Integration of Constraint Programming, Artificial Intelligence, and Operations Research N2 - Mixed Integer Programming (MIP) is NP-hard, and yet modern solvers often solve large real-world problems within minutes. This success can partially be attributed to heuristics. Since their behavior is highly instance-dependent, relying on hard-coded rules derived from empirical testing on a large heterogeneous corpora of benchmark instances might lead to sub-optimal performance. In this work, we propose an online learning approach that adapts the application of heuristics towards the single instance at hand. We replace the commonly used static heuristic handling with an adaptive framework exploiting past observations about the heuristic’s behavior to make future decisions. In particular, we model the problem of controlling Large Neighborhood Search and Diving – two broad and complex classes of heuristics – as a multi-armed bandit problem. Going beyond existing work in the literature, we control two different classes of heuristics simultaneously by a single learning agent. We verify our approach numerically and show consistent node reductions over the MIPLIB 2017 Benchmark set. For harder instances that take at least 1000 seconds to solve, we observe a speedup of 4%. Y1 - 2023 U6 - https://doi.org/10.1007/978-3-031-33271-5_8 VL - 13884 SP - 114 EP - 123 PB - Springer, Cham ER - TY - CHAP A1 - Gasse, Maxime A1 - Bowly, Simon A1 - Cappart, Quentin A1 - Charfreitag, Jonas A1 - Charlin, Laurent A1 - Chételat, Didier A1 - Chmiela, Antonia A1 - Dumouchelle, Justin A1 - Gleixner, Ambros A1 - Kazachkov, Aleksandr M. A1 - Khalil, Elias A1 - Lichocki, Pawel A1 - Lodi, Andrea A1 - Lubin, Miles A1 - Maddison, Chris J. A1 - Christopher, Morris A1 - Papageorgiou, Dimitri J. A1 - Parjadis, Augustin A1 - Pokutta, Sebastian A1 - Prouvost, Antoine A1 - Scavuzzo, Lara A1 - Zarpellon, Giulia A1 - Yang, Linxin A1 - Lai, Sha A1 - Wang, Akang A1 - Luo, Xiaodong A1 - Zhou, Xiang A1 - Huang, Haohan A1 - Shao, Shengcheng A1 - Zhu, Yuanming A1 - Zhang, Dong A1 - Quan, Tao A1 - Cao, Zixuan A1 - Xu, Yang A1 - Huang, Zhewei A1 - Zhou, Shuchang A1 - Binbin, Chen A1 - Minggui, He A1 - Hao, Hao A1 - Zhiyu, Zhang A1 - Zhiwu, An A1 - Kun, Mao T1 - The Machine Learning for Combinatorial Optimization Competition (ML4CO): results and insights T2 - Proceedings of Conference on Neural Information Processing Systems Y1 - 2022 ER - TY - CHAP A1 - Chmiela, Antonia A1 - Muñoz, Gonzalo A1 - Serrano, Felipe T1 - Monoidal strengthening and unique lifting in MIQCPs T2 - Integer Programming and Combinatorial Optimization. IPCO 2023. N2 - Using the recently proposed maximal quadratic-free sets and the well-known monoidal strengthening procedure, we show how to improve inter- section cuts for quadratically-constrained optimization problems by exploiting integrality requirements. We provide an explicit construction that allows an efficient implementation of the strengthened cuts along with computational results showing their improvements over the standard intersection cuts. We also show that, in our setting, there is unique lifting which implies that our strengthening procedure is generating the best possible cut coefficients for the integer variables. Y1 - 2023 U6 - https://doi.org/10.1007/978-3-031-32726-1_7 VL - 13904 SP - 87 EP - 99 ER - TY - CHAP A1 - Chmiela, Antonia A1 - Muñoz, Gonzalo A1 - Serrano, Felipe T1 - On the implementation and strengthening of intersection cuts for QCQPs T2 - Integer Programming and Combinatorial Optimization: 22nd International Conference, IPCO 2021 N2 - The generation of strong linear inequalities for QCQPs has been recently tackled by a number of authors using the intersection cut paradigm - a highly studied tool in integer programming whose flexibility has triggered these renewed efforts in non-linear settings. In this work, we consider intersection cuts using the recently proposed construction of maximal quadratic-free sets. Using these sets, we derive closed-form formulas to compute intersection cuts which allow for quick cut-computations by simply plugging-in parameters associated to an arbitrary quadratic inequality being violated by a vertex of an LP relaxation. Additionally, we implement a cut-strengthening procedure that dates back to Glover and evaluate these techniques with extensive computational experiments. Y1 - 2021 U6 - https://doi.org/10.1007/978-3-030-73879-2_10 VL - 22 SP - 134 EP - 147 ER - TY - JOUR A1 - Gorgulla, Christoph A1 - Garza, Alejandro J. A1 - Kapil, Venkat A1 - Fackeldey, Konstantin T1 - QUASAR: A Flexible QM-MM Method for Biomolecular Systems based on Restraining Spheres JF - Computer Physics Communications N2 - Quantum mechanical models of molecules theoretically offer unprecedented accuracy in predicting values associated with these systems, including the free energy of interaction between two molecules. However, high-accuracy quantum mechanical methods are computationally too expensive to be applied to larger systems, including most biomolecular systems such as proteins. To circumvent this challenge, the hybrid quantum mechanics/molecular mechanics (QM/MM) method was developed, allowing one to treat only the most important part of the system on the quantum mechanical level and the remaining part on the classical level. To date, QM/MM simulations for biomolecular systems have been carried out almost exclusively on the electronic structure level, neglecting nuclear quantum effects (NQEs). Yet NQEs can play a major role in biomolecular systems [1]. Here, we present i-QI, a QM/MM client for the path integral molecular dynamics (PIMD) software i-PI [2, 3, 4]. i-QI allows for carrying out QM/MM simulations simultaneously, allowing for the inclusion of electronic as well as nuclear quantum effects. i-QI implements a new QM/MM scheme based on constraining potentials called QUASAR, which allows handling diffusive systems, such as biomolecules solvated in water solvent. The QUASAR method is suitable in particular when the properties of interest are equilibrium properties, such as the free energy of binding. i-QI is freely available and open source, and we demonstrate it on a test system. KW - QM-MM Methods KW - Path Integral KW - biomolecular systems KW - CADD KW - Free Energy KW - Binding Y1 - 2025 U6 - https://doi.org/10.1016/j.cpc.2025.109949 SN - 0010-4655 VL - 320 ER - TY - JOUR A1 - Carderera, Alejandro A1 - Pokutta, Sebastian A1 - Schütte, Christof A1 - Weiser, Martin T1 - An efficient first-order conditional gradient algorithm in data-driven sparse identification of nonlinear dynamics to solve sparse recovery problems under noise JF - Journal of Computational and Applied Mathematics N2 - Governing equations are essential to the study of nonlinear dynamics, often enabling the prediction of previously unseen behaviors as well as the inclusion into control strategies. The discovery of governing equations from data thus has the potential to transform data-rich fields where well-established dynamical models remain unknown. This work contributes to the recent trend in data-driven sparse identification of nonlinear dynamics of finding the best sparse fit to observational data in a large library of potential nonlinear models. We propose an efficient first-order Conditional Gradient algorithm for solving the underlying optimization problem. In comparison to the most prominent alternative framework, the new framework shows significantly improved performance on several essential issues like sparsity-induction, structure-preservation, noise robustness, and sample efficiency. We demonstrate these advantages on several dynamics from the field of synchronization, particle dynamics, and enzyme chemistry. Y1 - 2025 U6 - https://doi.org/10.1016/j.cam.2025.116675 VL - 470 ER - TY - CHAP A1 - Schummel, Philip A1 - Teichmann, Malte A1 - Gonnermann-Müller, Jana T1 - Specifying ten roles of using chatgpt in secondary education: a teacher´s perspective T2 - Proceedings of the European Conference on Information Systems N2 - ChatGPT can benefit education; however, challenges arise that demand competent and responsible usage. Competence development needs to start in schools, with the teacher being the gatekeeper for integrating it into the teaching process. Existing research suggests that schoolteachers lack specific guidance on integrating ChatGPT into teaching, as current discussions remain high-level and omit specific use cases throughout the entire teaching process. To guide an informed usage, this paper presents the results of a systematic literature review, analyzing 38 selected papers on investigating ChatGPT in schools. This selection is based on rigorously defined criteria, adhering to the PRISMA guidelines, initially screening 1075 papers. The central value of this paper is to aggregate research into ten roles for secondary teachers on using ChatGPT in schools, presenting corresponding use cases throughout the teaching process. Future research validates the ten roles, conducting interviews with teachers to present an exhaustive framework for integrating ChatGPT in schoolteacher practice. Y1 - 2025 UR - https://aisel.aisnet.org/ecis2025/education/education/3/ ER - TY - CHAP A1 - Lasby, Mike A1 - Zimmer, Max A1 - Pokutta, Sebastian A1 - Schultheis, Erik T1 - Compressed sparse tiles for memory-efficient unstructured and semi-structured sparsity T2 - Proceedings of the ICLR Workshop on Sparsity in LLMs Y1 - 2025 UR - https://openreview.net/forum?id=iso0KV2HVq ER - TY - CHAP A1 - Fukuda, Takuma A1 - Kera, Hiroshi A1 - Kawamoto, Kazuhiko T1 - Adapter Merging with Centroid Prototype Mapping for Scalable Class-Incremental Learning T2 - 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Y1 - 2025 U6 - https://doi.org/10.1109/CVPR52734.2025.00460 SP - 4884 EP - 4893 ER - TY - CHAP A1 - Haase, Jennifer A1 - Hanel, Paul H. P. A1 - Pokutta, Sebastian T1 - S-DAT: a multilingual, GenAI-driven framework for automated divergent thinking assessment T2 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES) Y1 - 2025 VL - 8 SP - 1194 EP - 1205 ER - TY - JOUR A1 - Wirth, Elias A1 - Peña, Javier A1 - Pokutta, Sebastian T1 - Fast convergence of Frank-Wolfe algorithms on polytopes JF - INFORMS Journal on Mathematics of Operations Research Y1 - 2025 U6 - https://doi.org/10.1287/moor.2024.0580 ER - TY - JOUR A1 - Woodstock, Zev A1 - Pokutta, Sebastian T1 - Splitting the conditional gradient algorithm JF - SIAM Journal on Optimization Y1 - 2025 U6 - https://doi.org/10.1137/24M1638008 VL - 35 IS - 1 SP - 347 EP - 368 ER - TY - JOUR A1 - Gonnermann-Müller, Jana A1 - Haase, Jennifer A1 - Leins, Nicolas A1 - Igel, Moritz A1 - Fackeldey, Konstantin A1 - Pokutta, Sebastian T1 - FACET: Multi-Agent AI Supporting Teachers in Scaling Differentiated Learning for Diverse Students JF - arXiv N2 - Classrooms are becoming increasingly heterogeneous, comprising learners with diverse performance and motivation levels, language proficiencies, and learning differences such as dyslexia and ADHD. While teachers recognize the need for differentiated instruction, growing workloads create substantial barriers, making differentiated instruction an ideal that is often unrealized in practice. Current AI educational tools, which promise differentiated materials, are predominantly student-facing and performance-centric, ignoring other aspects that shape learning outcomes. We introduce FACET, a teacher-facing multi-agent framework designed to address these gaps by supporting differentiation that accounts for motivation, performance, and learning differences. Developed with educational stakeholders from the outset, the framework coordinates four specialized agents, including learner simulation, diagnostic assessment, material generation, and evaluation within a teacher-in-the-loop design. School principals (N = 30) shaped system requirements through participatory workshops, while in-service K-12 teachers (N = 70) evaluated material quality. Mixed-methods evaluation demonstrates strong perceived value for inclusive differentiation. Practitioners emphasized both the urgent need arising from classroom heterogeneity and the importance of maintaining pedagogical autonomy as a prerequisite for adoption. We discuss implications for future school deployment and outline partnerships for longitudinal classroom implementation. Y1 - 2026 U6 - https://doi.org/https://arxiv.org/abs/2601.22788 ER - TY - CHAP A1 - Ebert, Patricia A1 - Masing, Berenike A1 - Lindner, Niels A1 - Gleixner, Ambros T1 - Sorting Criteria for Line-based Periodic Timetabling Heuristics T2 - Operations Research Proceedings 2024. OR 2024 N2 - It is well-known that optimal solutions are notoriously hard to find for the Periodic Event Scheduling Problem (PESP), which is the standard mathematical formulation to optimize periodic timetables in public transport. We consider a class of incremental heuristics that have been demonstrated to be effective by Lindner and Liebchen (2023), however, for only one fixed sorting strategy of lines along which a solution is constructed. Thus, in this paper, we examine a variety of sortings based on the number, weight, weighted span, and lower bound of arcs, and test for each setting various combinations of the driving, dwelling, and transfer arcs of lines. Additionally, we assess the impact on the incremental extension of the event-activity network by minimizing resp. maximizing a connectivity measure between subsets of lines. We compare our 27 sortings on the railway instances of the benchmarking library PESPlib within the ConcurrentPESP solver framework. We are able to find five new incumbent solutions, resulting in improvements of up to 2%. Y1 - 2025 SP - 348 EP - 354 ER - TY - JOUR A1 - Halbig, Katrin A1 - Hoen, Alexander A1 - Gleixner, Ambros A1 - Witzig, Jakob A1 - Weninger, Dieter T1 - A diving heuristic for mixed-integer problems with unbounded semi-continuous variables JF - EURO Journal on Computational Optimization Y1 - 2025 U6 - https://doi.org/10.1016/j.ejco.2025.100107 VL - 13 ER - TY - JOUR A1 - Bestuzheva, Ksenia A1 - Gleixner, Ambros A1 - Achterberg, Tobias T1 - Efficient separation of RLT cuts for implicit and explicit bilinear terms JF - Mathematical Programming Y1 - 2025 U6 - https://doi.org/10.1007/s10107-024-02104-0 VL - 210 SP - 47 EP - 74 ER -