We develop theory and solution methodologies for linear and nonlinear mixed-integer optimization programs (MIPs). Our primary focus lies in enhancing the efficiency of integer and spatial branch-and-bound algorithms, which provide a general-purpose approach to finding provable global optima and coordinate within one framework components such as relaxations, cutting planes, primal heuristics, presolving procedures, and other solving techniques. Our group works on all these aspects and their interaction within the constraint integer programming solver SCIP. We also work on algorithms combining satisfiability and MIP techniques such as conflict analysis and domain propagation; on exact MIP and linear programming, guaranteeing that solutions are not invalidated by floating-point arithmetic errors; and on polynomial optimization problems.
🧑‍🎓 Members
bolusani (at) zib.de
ghannam (at) zib.de
miskovic (at) zib.de
hoen (at) zib.de
chmiela (at) zib.de
hendrych (at) zib.de
vigerske (at) zib.de
liding.xu (at) zib.de
ebert (at) zib.de
geis (at) zib.de
von.holly-ponientzietz (at) zib.de
dionisio (at) zib.de
🔬 Projects
We will investigate mixed-integer optimization with convex objectives using error-adaptive convex solvers in branch-and-bound. Focusing on improving lower bounds and balancing computational costs, we aim to develop a faster branch-and-bound methodology by leveraging modern MILP techniques and error-adaptive methods. Key aspects include warm-starting and controlled inexactness in early termination.
SynLab researches mathematical generalization of application-specific advances achieved in the Gas-, Rail– and MedLab of the research campus MODAL. The focus is on exact methods for solving a broad class of discrete-continuous optimization problems. This requires advanced techniques for structure recognition, consideration of nonlinear restrictions from practice, and the efficient implementation of mathematical algorithms on modern computer architectures. The results are bundled in a professional software package and complemented by a range of high-performance methods for specific applications with a high degree of innovation.
MiniMIP is an open source, machine learning oriented Mixed-Integer Programming (MIP) solver. We provide a range of interfaces for all aspects of solving MIPs (e.g. heuristics, cut generators, LP solvers), supplying users with a constant view of the internal state and allowing them to propose modifications that are integrated into the global state internally.
Heuristics play a crucial role in exact solvers for Mixed Integer Programming (MIP). However, the question of how to manage multiple MIP heuristics in a solver has not received sufficient attention. This project addresses the strategic management of primal heuristics in MIP solvers, aiming to replace static, hard-coded rules with dynamic, self-improving procedures.
The performance of modern mixed-integer program solvers is highly dependent on a number of interdependent individual components. Using tools from machine learning, we intend to develop an integrated framework that is able to capture interactions of individual decisions made in these components with the ultimate goal to improve performance.
Training artificial neural networks is a key optimization task in deep learning. To improve generalization, robustness, and explainability, we aim to compute globally optimal solutions. We will use integer programming methods, exploiting mixed-integer nonlinear programming and enhancing solving techniques like spatial branch-and-cut. Additionally, we'll leverage symmetry to reduce computational burden and ensure symmetry in solutions, and incorporate true sparsity using a mixed-integer nonlinear programming framework.
đź’¬ Talks and posters
Conference and workshop talks
- Sep 2024
- The Relax-and-Cut Framework in the SCIP Optimization Solver by Suresh Bolusani
OR Conference, Munich - Sep 2024
- What Is New in the SCIP Optimization Suite 9.0 by Ksenia Bestuzheva
OR Conference, Munich - Jul 2024
- Solving the Optimal Design Problem with Mixed-Integer Convex Methods by Deborah Hendrych
22nd Symposium on Experimental Algorithms (SEA), Vienna - Jul 2024
- Generalized Convexity Applied to Branch-and-Bound Algorithms for MINLPs by Ksenia Bestuzheva
33rd European Conference on Operational Research (EURO), Copenhagen - Jul 2024
- Recent Advances in the SCIP Optimization Solver by Suresh Bolusani
33rd European Conference on Operational Research (EURO), Copenhagen - Jul 2024
- Generalized Resolution Conflict Analysis in MIP Solvers by Gioni Mexi
25th International Symposium on Mathematical Programming (ISMP), Montréal - Jul 2024
- Polyhedrality Made Easy. Using General Cut Operators to Determine When Cut Closures Are Polyhedral by Antonia Chmiela
25th International Symposium on Mathematical Programming (ISMP), Montréal - Jul 2024
- Certifying MIP-Based Presolve Reductions for 0-1 Integer Linear Programs by Alexander Hoen
25th International Symposium on Mathematical Programming (ISMP), Montréal - May 2024
- Probabilistic Lookahead Strong Branching Via a Stochastic Abstract Branching Model by Gioni Mexi
21st CPAIOR Conference, Uppsala - May 2024
- Certifying MIP-Based Presolve Reductions for 0-1 Integer Linear Programs by Alexander Hoen
21st CPAIOR Conference, Uppsala - Apr 2024
- Updates in SCIP 9 by Gioni Mexi
SAP-ZIB-FAU Workshop, Walldorf - Mar 2024
- Efficient Relax-and-Cut Separation in a Branch-and-Cut Solver by Suresh Bolusani
INFORMS Optimization Society Conference (IOS), Houston, TX - Jan 2024
- Monoidal Strengthening and Unique Lifting in MIQCPs by Antonia Chmiela
Combinatorial Optimization Workshop (Aussois), Aussois - Nov 2023
- Relax-and-Cut Framework-based Lagromory Separator in SCIP by Suresh Bolusani
ZIB-Siemens Workshop, Berlin - Nov 2023
- Recent Advances in SCIP Optimization Suite by Alexander Hoen
ZIB-Siemens Workshop, Berlin - Sep 2023
- Lagromory Separator in SCIP by Suresh Bolusani
SAP-ZIB-FAU Workshop, Walldorf - Sep 2023
- SCIP Beyond 8.0 by Ksenia Bestuzheva
7th ZIB-IMI-ISM-NUS-RIKEN-MODAL Workshop, Berlin [PDF] - Sep 2023
- Recent Advances in SCIP by Alexander Hoen
SAP-ZIB-FAU Workshop, Walldorf - Sep 2023
- Structured Constrained Nonlinear Optimization with Frank-Wolfe Methods by Mathieu Besançon
TES - Mathematical Optimization for ML, Berlin - Sep 2023
- Product and Factor Filtering for RLT for Bilinear and Mixed-Integer Problems by Ksenia Bestuzheva
OR Conference, Hamburg [PDF] - Aug 2023
- Scylla: A Matrix-free Fix-Propagate-and-Project Heuristic for Mixed Integer Optimization by Suresh Bolusani
OR Conference, Hamburg - Aug 2023
- Experiments on Sparsity & Sparsification in Cutting Plane Selection by Mathieu Besançon
OR Conference, Hamburg - Aug 2023
- Improving Conflict Analysis in MIP Solvers by Pseudo-Boolean Reasoning by Gioni Mexi
29th CP Conference, Toronto [PDF] - Jul 2023
- Improving Conflict Analysis in MIP Solvers by Pseudo-Boolean Reasoning by Gioni Mexi
14th Pragmatics of SAT international workshop [PDF] - Jul 2023
- On Performance Variability in Pseudo-Boolean Solving and the Impact of Trivial Model Simplifications by Alexander Hoen
Pragmatics of SAT 2023 - Jul 2023
- Modelling of Piece-wise Linear Concave Constraints in Continous Covering Problems by Liding Xu
33rd European Conference on Operational Research (EURO), Copenhagen - Jun 2023
- Efficient Separation of RLT Cuts for Implicit and Explicit Bilinear Products by Ksenia Bestuzheva
24th IPCO Conference, Madison [PDF] - Jun 2023
- Recent Developments in SCIP by Suresh Bolusani
SIAM conference on optimization (SIAMOP) - Jun 2023
- Monoidal Strengthening and Unique Lifting in MIQCPs by Antonia Chmiela
24th IPCO Conference, Madison - May 2023
- Perspective Cuts for Generalized On/Off Constraints by Ksenia Bestuzheva
20th Mixed Integer Programming European Workshop (MIP) [PDF] - May 2023
- MIPcc23: The MIP Workshop 2023 Computational Competition by Suresh Bolusani
20th Mixed Integer Programming European Workshop (MIP) - May 2023
- Online Learning for Scheduling MIP Heuristics by Antonia Chmiela
ZIB-Siemens Workshop, Munich - May 2023
- The MIP 2023 Computational Competition by Ambros Gleixner
ZIB-Siemens Workshop, Munich - May 2023
- Online Learning for Scheduling MIP Heuristics by Antonia Chmiela
20th CPAIOR Conference - Feb 2023
- Cutting Plane Selection with Analytic Centers by Mathieu Besançon
ROADEF Conference, Rennes - Jan 2023
- Recent Advances in SCIP by Gioni Mexi
SAP-ZIB-FAU Workshop, Walldorf - Jan 2023
- Online Learning for Scheduling MIP Heuristics by Antonia Chmiela
SAP-ZIB Workshop, Walldorf - Jan 2023
- Recent Advances in SCIP by Alexander Hoen
SAP-ZIB-FAU Workshop, Walldorf - Jan 2023
- Cutting Plane Selection with Analytic Centers by Mathieu Besançon
Combinatorial Optimization Workshop (Aussois), Aussois - Jan 2023
- Tighter SONC Bounds for Polynomial Optimization Problems with Bounded Variable Domains by Ksenia Bestuzheva
Combinatorial Optimization Workshop (Aussois), Aussois [PDF] - Jan 2023
- Talk by Antonia Chmiela
Combinatorial Optimization Workshop (Aussois), Aussois - Nov 2022
- Strengthening Dual Bounds in Branch-and-Bound by SONC Certificates by Ksenia Bestuzheva
Let's SCIP it! (SCIP), Berlin [PDF] - Nov 2022
- Monoidal Strengthening for Intersection Cuts Using Maximal Quadratic-Free Sets by Antonia Chmiela
Let's SCIP it! (SCIP), Berlin - Sep 2022
- Strengthening SONC Relaxations with Constraints Derived From Variable Bounds by Ksenia Bestuzheva
HUGO 2022 – XV. Workshop on Global Optimization (HUGO 2022), Szeged [PDF] - Jul 2022
- New Developments in the SCIP Optimization Suite 8 by Ksenia Bestuzheva
32nd European Conference on Operational Research (EURO), Espoo [PDF] - Jul 2022
- Feasibility Pump Using Multiple Reference Vectors And New Scaling by Gioni Mexi
32nd European Conference on Operational Research (EURO), Espoo - Oct 2021
- Talk by Antonia Chmiela
INFORMS Annual Meeting (INFORMS), Anaheim - Sep 2021
- Recent Developments in SCIP by Ksenia Bestuzheva
5th ZIB-IMI-ISM-NUS-RIKEN-MODAL Workshop, Berlin [PDF] - Aug 2021
- Solving MINLPs with SCIP by Ksenia Bestuzheva
22nd IFORS Conference [PDF] - Jul 2021
- A Computational Study Of Perspective Cuts by Ksenia Bestuzheva
31st European Conference on Operational Research (EURO), Athens [PDF] - Jul 2021
- Learning to Schedule Heuristics in Branch and Bound by Antonia Chmiela
31st European Conference on Operational Research (EURO), Athens - Jun 2021
- Reformulation-Linearisation Technique for Implicit Bilinear Relations by Ksenia Bestuzheva
Mixed-Integer Nonlinear Programming Workshop (MINLP) [PDF] - May 2021
- On the Implementation and Strengthening of Intersection Cuts for QCQPs by Antonia Chmiela
22nd IPCO Conference, online - Sep 2020
- Mixed-Integer Nonlinear Programming by Ksenia Bestuzheva
4th Computational Optimization at Work (CO@Work), Berlin [PDF] - Jun 2020
- Nonlinear Constraints in SCIP by Ksenia Bestuzheva
SCIP Workshop (SCIP), Berlin [PDF]
Research seminar talks
- Nov 2024
- New Perspectives on Invexity and Its Algorithmic Applications by Ksenia Bestuzheva
Group seminar KTH Royal Institute of Technology, Stockholm - Nov 2024
- A Reformulation-Linearization Technique Framework for Problems with Bilinear Terms by Ksenia Bestuzheva
Discrete Optimization Talks, online - Nov 2024
- Solving the Optimal Design Problem with Mixed-Integer Convex Methods by Deborah Hendrych
GHOST Research Seminar (GHOST), Grenoble - Oct 2024
- New Perspectives on Invexity and Its Algorithmic Applications by Ksenia Bestuzheva
Group seminar Laboratoire d'Informatique de Paris-Nord, Paris - Jul 2024
- Solving the Optimal Design Problem with Mixed-Integer Convex Methods by Deborah Hendrych
NASPDE Seminar, Berlin - May 2024
- Solving the Optimal Design Problem with Mixed-Integer Convex Methods by Deborah Hendrych
MATH+ Spotlight talks, Berlin - Dec 2023
- Solving the Optimal Experiment Design Problems with Mixed-Integer Frank-Wolfe-based Methods by Deborah Hendrych
IOL Research Seminar (IOL), Berlin - Nov 2023
- Constrained Nonlinear Optimization with Frank-Wolfe by Mathieu Besançon
Group seminar Laboratoire Jean Kuntzmann, Grenoble - Mar 2023
- Cutting Plane Selection with Analytic Centers by Mathieu Besançon
Department seminar, EDGE, Institut Mathématique de Bordeaux and Inria, Bordeaux - Mar 2023
- Convex Optimization Techniques for Mixed-integer Nonlinear Problems by Mathieu Besançon
Department seminar, DĂ©partement d'Informatique de Polytechnique, Palaiseau - Feb 2023
- Generalized Benders' Algorithm for Mixed Integer Bilevel Linear Optimization by Suresh Bolusani
Department seminar, Industrial Engineering and Operations Research, IIT Bombay
Poster presentations
- May 2024
- MIP-DD. A Delta Debugger for Mixed Integer Programming Solvers by Alexander Hoen
21st CPAIOR Conference, Uppsala - Apr 2024
- Convex Solver Adaptivity for Mixed-Integer Optimization by Deborah Hendrych
5th Women in Optimization 2024 (WiO), Erlangen - Feb 2023
- Learning to Schedule MIP Heuristics by Antonia Chmiela
IPAM Workshop on Deep Learning and Combinatorial Optimization - May 2022
- Monoidal Strengthening for Intersection Cuts Using Maximal Quadratic-Free Sets by Antonia Chmiela
19th Mixed Integer Programming European Workshop (MIP) - Dec 2021
- Learning to Schedule Heuristics in Branch-and-Bound by Antonia Chmiela
conference on neural information processing systems (NeurIPS) - May 2021
- Learning to Schedule Heuristics in Branch-and-Bound by Antonia Chmiela
18th Mixed Integer Programming European Workshop (MIP)
đź“ť Publications and preprints
- Bolusani, S., Besançon, M., Bestuzheva, K., Chmiela, A., DionĂsio, J., Donkiewicz, T., van Doornmalen, J., Eifler, L., Ghannam, M., Gleixner, A., Graczyk, C., Halbig, K., Hedtke, I., Hoen, A., Hojny, C., van der Hulst, R., Kamp, D., Koch, T., Kofler, K., … Xu, L. (2024). The SCIP Optimization Suite 9.0 (ZIB Report No. 24-02-29). Zuse Institute Berlin.
[URL]
[arXiv]
[code]
[BibTeX]
- Bestuzheva, K., Gleixner, A., and Achterberg, T. (2024). Efficient Separation of RLT Cuts for Implicit and Explicit Bilinear Terms. Mathematical Programming.
DOI: https://doi.org/10.1007/s10107-024-02104-0
[arXiv]
[BibTeX]
- Deza, A., Pokutta, S., and Pournin, L. (2024). The Complexity of Geometric Scaling. Operations Research Letters, 52.
DOI: 10.1016/j.orl.2023.11.010
[arXiv]
[BibTeX]
- Bolusani, S., Besançon, M., Gleixner, A., Berthold, T., D’Ambrosio, C., Muñoz, G., Paat, J., and Thomopulos, D. (2024). The MIP Workshop 2023 Computational Competition on Reoptimization. Mathematical Programming Computation.
DOI: 10.1007/s12532-024-00256-w
[arXiv]
[BibTeX]
- Chmiela, A., Muñoz, G., and Serrano, F. (2024). Monoidal Strengthening and Unique Lifting in MIQCPs. Mathematical Programming B.
DOI: 10.1007/s10107-024-02112-0
[URL]
[BibTeX]
- Eifler, L., and Gleixner, A. (2024). Safe and Verified Gomory Mixed Integer Cuts in a Rational MIP Framework. SIAM Journal on Optimization, 34(1), 742–763.
DOI: 10.1137/23M156046X
[URL]
[arXiv]
[BibTeX]
- Eifler, L., Nicolas-Thouvenin, J., and Gleixner, A. (2024). Combining Precision Boosting with LP Iterative Refinement for Exact Linear Optimization. INFORMS Journal on Computing.
DOI: 10.1007/s10107-024-02104-0
[arXiv]
[BibTeX]
- Hendrych, D., Besançon, M., and Pokutta, S. (2024). Solving the Optimal Experiment Design Problem with Mixed-integer Convex Methods. Proceedings of the Symposium on Experimental Algorithms.
DOI: 10.4230/LIPIcs.SEA.2024.16
[arXiv]
[code]
[BibTeX]
- Mexi, G., Shamsi, S., Besançon, M., and le Bodic, P. (2024). Probabilistic Lookahead Strong Branching Via a Stochastic Abstract Branching Model. Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research.
[arXiv]
[BibTeX]
- Göß, A., Martin, A., Pokutta, S., and Sharma, K. (2024). Norm-induced Cuts: Optimization with Lipschitzian Black-box Functions.
[URL]
[arXiv]
[BibTeX]
- Bolusani, S., Mexi, G., Besançon, M., and Turner, M. (2024). A Multi-Reference Relaxation Enforced Neighborhood Search Heuristic in SCIP.
[arXiv]
[BibTeX]
- Borst, S., Eifler, L., and Gleixner, A. (2024). Certified Constraint Propagation and Dual Proof Analysis in a Numerically Exact MIP Solver.
[arXiv]
[BibTeX]
- Eifler, L., Witzig, J., and Gleixner, A. (2024). Branch and Cut for Partitioning a Graph Into a Cycle of Clusters. Proceedings of the International Symposium on Combinatorial Optimization.
DOI: 10.1007/978-3-031-60924-4_8
[arXiv]
[BibTeX]
- Tjusila, G., Besançon, M., Turner, M., and Koch, T. (2024). How Many Clues To Give? A Bilevel Formulation For The Minimum Sudoku Clue Problem. Operations Research Letters.
DOI: 10.1016/j.orl.2024.107105
[URL]
[arXiv]
[BibTeX]
- Ghannam, M., Mexi, G., Lam, E., and Gleixner, A. (2024). Branch and Price for the Length-constrained Cycle Partition Problem. Proceedings of the INFORMS Optimization Society Conference.
[URL]
[arXiv]
[BibTeX]
- Halbig, K., Hoen, A., Gleixner, A., Witzig, J., and Weninger, D. (2024). A Diving Heuristic for Mixed-integer Problems with Unbounded Semi-continuous Variables.
[arXiv]
[BibTeX]
- Hoen, A., Kamp, D., and Gleixner, A. (2024). MIP-DD: A Delta Debugger for Mixed Integer Programming Solvers.
[arXiv]
[BibTeX]
- Hoen, A., Oertel, A., Gleixner, A., and Nordström, J. (2024). Certifying MIP-based Presolve Reductions for 0-1 Integer Linear Programs. Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 310–328.
DOI: 10.1007/978-3-031-60597-0_20
[arXiv]
[BibTeX]
- Mexi, G., Serrano, F., Berthold, T., Gleixner, A., and Nordström, J. (2024). Cut-based Conflict Analysis in Mixed Integer Programming.
[arXiv]
[BibTeX]
- Sharma, K., Hendrych, D., Besançon, M., and Pokutta, S. (2024). Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe. Proceedings of the INFORMS Optimization Society Conference.
[arXiv]
[BibTeX]
- Xu, L., and D’Ambrosio, C. (2024). Formulations of the Continuous Set-covering Problem on Networks: a Comparative Study.
[arXiv]
[BibTeX]
- Xu, L., and Liberti, L. (2024). Relaxations for Binary Polynomial Optimization Via Signed Certificates.
[arXiv]
[BibTeX]
- Liberti, L., Iommazzo, G., Lavor, C., and Maculan, N. (2023). Cycle-based Formulations in Distance Geometry. Open Journal of Mathematical Optimization, 4(1).
DOI: 10.5802/ojmo.18
[arXiv]
[BibTeX]
- Bestuzheva, K., Gleixner, A., and Vigerske, S. (2023). A Computational Study of Perspective Cuts. Mathematical Programming Computation, 15, 703–731.
DOI: 10.1007/s12532-023-00246-4
[URL]
[arXiv]
[BibTeX]
- Bestuzheva, K., Gleixner, A., and Achterberg, T. (2023). Efficient Separation of RLT Cuts for Implicit and Explicit Bilinear Terms. Proceedings of the Conference on Integer Programming and Combinatorial Optimization, 14–28.
DOI: 10.1007/978-3-031-32726-1_2
[arXiv]
[BibTeX]
- Gleixner, A., Gottwald, L., and Hoen, A. (2023). PaPILO: a Parallel Presolving Library for Integer and Linear Programming with Multiprecision Support. INFORMS Journal on Computing.
DOI: 10.1287/ijoc.2022.0171
[arXiv]
[BibTeX]
- Turner, M., Berthold, T., Besançon, M., and Koch, T. (2023). Cutting Plane Selection with Analytic Centers and Multiregression. Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research.
[arXiv]
[BibTeX]
- Berthold, T., Mexi, G., and Salvagnin, D. (2023). Using Multiple Reference Vectors and Objective Scaling in the Feasibility Pump. EURO Journal on Computational Optimization, 11.
DOI: 10.1016/j.ejco.2023.100066
[BibTeX]
- Bestuzheva, K., Chmiela, A., MĂĽller, B., Serrano, F., Vigerske, S., and Wegscheider, F. (2023). Global Optimization of Mixed-integer Nonlinear Programs with SCIP 8.0. Journal of Global Optimization.
DOI: 10.1007/s10898-023-01345-1
[URL]
[arXiv]
[BibTeX]
- Bestuzheva, K., Besançon, M., Chen, W.-K., Chmiela, A., Donkiewicz, T., van Doornmalen, J., Eifler, L., Gaul, O., Gamrath, G., Gleixner, A., Gottwald, L., Graczyk, C., Halbig, K., Hoen, A., Hojny, C., van der Hulst, R., Koch, T., Lübbecke, M., Maher, S. J., … Witzig, J. (2023). Enabling Research Through the SCIP Optimization Suite 8.0. ACM Transactions on Mathematical Software.
DOI: 10.1145/3585516
[arXiv]
[BibTeX]
- Chmiela, A., Gleixner, A., Lichocki, P., and Pokutta, S. (2023). Online Learning for Scheduling MIP Heuristics. Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 114–123.
DOI: 10.1007/978-3-031-33271-5_8
[arXiv]
[BibTeX]
- Chmiela, A., Muñoz, G., and Serrano, F. (2023). Monoidal Strengthening and Unique Lifting in MIQCPs. Proceedings of the Conference on Integer Programming and Combinatorial Optimization.
[URL]
[BibTeX]
- Eifler, L., and Gleixner, A. (2023). A Computational Status Update for Exact Rational Mixed Integer Programming. Mathematical Programming, 197, 793–812.
DOI: 10.1007/s10107-021-01749-5
[arXiv]
[BibTeX]
- Ghannam, M., and Gleixner, A. (2023). Hybrid Genetic Search for Dynamic Vehicle Routing with Time Windows. Proceedings of the Conference of the Society for Operations Research in Germany.
[arXiv]
[BibTeX]
- Mexi, G., Berthold, T., Gleixner, A., and Nordström, J. (2023). Improving Conflict Analysis in MIP Solvers by Pseudo-Boolean Reasoning. Proceedings of the 29th International Conference on Principles and Practice of Constraint Programming (CP 2023), 280, 27:1–27:19,
DOI: 10.4230/LIPIcs.CP.2023.27
[arXiv]
[BibTeX]
- Mexi, G., Besançon, M., Bolusani, S., Chmiela, A., Hoen, A., and Gleixner, A. (2023). Scylla: a Matrix-free Fix-propagate-and-project Heuristic for Mixed-integer Optimization. Proceedings of the Conference of the Society for Operations Research in Germany.
[arXiv]
[BibTeX]
- Turner, M., Berthold, T., Besançon, M., and Koch, T. (2023). Branching Via Cutting Plane Selection: Improving Hybrid Branching.
[arXiv]
[BibTeX]
- Turner, M., Berthold, T., and Besançon, M. (2023). A Context-Aware Cutting Plane Selection Algorithm for Mixed-Integer Programming. Proceedings of the Conference of the Society for Operations Research in Germany.
[arXiv]
[BibTeX]
- Turner, M., Chmiela, A., Koch, T., and Winkler, M. (2023). PySCIPOpt-ML: Embedding Trained Machine Learning Models Into Mixed-integer Programs.
[arXiv]
[BibTeX]
- van Doornmalen, J., Eifler, L., Gleixner, A., and Hojny, C. (2023). A Proof System for Certifying Symmetry and Optimality Reasoning in Integer Programming.
[arXiv]
[BibTeX]
- Gasse, M., Bowly, S., Cappart, Q., Charfreitag, J., Charlin, L., Chételat, D., Chmiela, A., Dumouchelle, J., Gleixner, A., Kazachkov, A. M., Khalil, E., Lichocki, P., Lodi, A., Lubin, M., Maddison, C. J., Christopher, M., Papageorgiou, D. J., Parjadis, A., Pokutta, S., … Kun, M. (2022). The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. Proceedings of the Conference on Neural Information Processing Systems, 176, 220–231.
[URL]
[arXiv]
[BibTeX]
- Sofranac, B., Gleixner, A., and Pokutta, S. (2022). Accelerating Domain Propagation: An Efficient GPU-parallel Algorithm Over Sparse Matrices. Parallel Computing, 109, 102874.
DOI: 10.1016/j.parco.2021.102874
[arXiv]
[summary]
[BibTeX]
- Bolusani, S., and Ralphs, T. K. (2022). A Framework for Generalized Benders’ Decomposition and Its Applications to Multilevel Optimization. Mathematical Programming, 196, 389–426.
DOI: 10.1007/s10107-021-01763-7
[arXiv]
[BibTeX]
- Sofranac, B., Gleixner, A., and Pokutta, S. (2022). An Algorithm-independent Measure of Progress for Linear Constraint Propagation. Constraints, 27, 432–455.
DOI: 10.1007/s10601-022-09338-9
[arXiv]
[BibTeX]
- Chmiela, A., Muñoz, G., and Serrano, F. (2022). On the Implementation and Strengthening of Intersection Cuts for QCQPs. Mathematical Programming B, 197, 549–586.
DOI: 10.1007/s10107-022-01808-5
[BibTeX]
- Eifler, L., Gleixner, A., and Pulaj, J. (2022). A Safe Computational Framework for Integer Programming Applied to Chvátal’s Conjecture. ACM Transactions on Mathematical Software, 48(2), 1–12.
DOI: 10.1145/3485630
[arXiv]
[BibTeX]
- Hendrych, D., Troppens, H., Besançon, M., and Pokutta, S. (2022). Convex Integer Optimization with Frank-Wolfe Methods.
[arXiv]
[slides]
[code]
[BibTeX]
- Hoppmann-Baum, K., Burdakov, O., Mexi, G., Casselgren, C. J., and Koch, T. (2022). Length-Constrained Cycle Partition with an Application to UAV Routing. Optimization Methods and Software.
DOI: 10.1080/10556788.2022.2053972
[BibTeX]
- Iommazzo, G., D’Ambrosio, C., Frangioni, A., and Liberti, L. (2022). Algorithm Configuration Problem. In Encyclopedia of Optimization (pp. 1–8).
DOI: 10.1007/978-3-030-54621-2_749-1
[arXiv]
[BibTeX]
- Kossen, T., Hirzel, M. A., Madai, V. I., Boenisch, F., Hennemuth, A., Hildebrand, K., Pokutta, S., Sharma, K., Hilbert, A., Sobesky, J., Galinovic, I., Khalil, A. A., Fiebach, J. B., and Frey, D. (2022). Towards Sharing Brain Images: Differentially Private TOF-MRA Images with Segmentation Labels Using Generative Adversarial Networks. Frontiers in Artificial Intelligence.
DOI: 10.3389/frai.2022.813842
[BibTeX]
- Bestuzheva, K., Gleixner, A., and Völker, H. (2022). Strengthening SONC Relaxations with Constraints Derived From Variable Bounds. Proceedings of the Proceedings of the Hungarian Global Optimization Workshop HUGO 2022, 41–44.
[URL]
[arXiv]
[BibTeX]
- Bestuzheva, K., Besançon, M., Chen, W.-K., Chmiela, A., Donkiewicz, T., van Doornmalen, J., Eifler, L., Gaul, O., Gamrath, G., Gleixner, A., Gottwald, L., Graczyk, C., Halbig, K., Hoen, A., Hojny, C., van der Hulst, R., Koch, T., Lübbecke, M., Maher, S. J., … Witzig, J. (2021). The SCIP Optimization Suite 8.0 (ZIB Report No. 21-41). Zuse Institute Berlin.
[URL]
[arXiv]
[code]
[BibTeX]
- Chmiela, A., Khalil, E. B., Gleixner, A., Lodi, A., and Pokutta, S. (2021). Learning to Schedule Heuristics in Branch-and-bound. Proceedings of the Conference on Neural Information Processing Systems, 34, 24235–24246.
[URL]
[arXiv]
[poster]
[BibTeX]
- Bolusani, S., Coniglio, S., Ralphs, T. K., and Tahernejad, S. (2021). A Unified Framework for Multistage Mixed Integer Linear Optimization.
[arXiv]
[BibTeX]
- Ramin, E., Bestuzheva, K., Gargalo, C., Ramin, D., Schneider, C., Ramin, P., Flores-Alsina, X., Andersen, M., and Gernaey, K. (2021). Incremental Design of Water Symbiosis Networks with Prior Knowledge: the Case of an Industrial Park in Kenya. Science of the Total Environment, 751.
DOI: 10.1016/j.scitotenv.2020.141706
[BibTeX]
- Sofranac, B., Gleixner, A., and Pokutta, S. (2021). An Algorithm-independent Measure of Progress for Linear Constraint Propagation. Proceedings of the International Conference on Principles and Practice of Constraint Programming, 52:1–17.
DOI: 10.4230/LIPIcs.CP.2021.52
[URL]
[arXiv]
[video]
[BibTeX]
- Chmiela, A., Muñoz, G., and Serrano, F. (2021). On the Implementation and Strengthening of Intersection Cuts for QCQPs. Proceedings of the Conference on Integer Programming and Combinatorial Optimization, 134–147.
DOI: 10.1007/978-3-030-73879-2_10
[BibTeX]
- Hoppmann-Baum, K., Mexi, G., Burdakov, O., Casselgren, C. J., and Koch, T. (2020). Minimum Cycle Partition with Length Requirements. Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 12296, 273–282.
DOI: 10.1007/978-3-030-58942-4_18
[BibTeX]
- Sofranac, B., Gleixner, A., and Pokutta, S. (2020). Accelerating Domain Propagation: An Efficient GPU-parallel Algorithm Over Sparse Matrices. Proceedings of the 10th IEEE/ACM Workshop on Irregular Applications: Architectures and Algorithms, IA3 2020, 1–11.
DOI: 10.1109/IA351965.2020.00007
[arXiv]
[summary]
[slides]
[video]
[BibTeX]