Christoph Graczyk

My research is devoted to the intersection of optimization techniques and machine learning, aiming to distill qualitative insights from the inherent optimality guarantees of traditional global optimization methods. I am currently developing MiniMIP, an open-source standalone Mixed Integer Linear Programming Solver, to seamlessly integrate machine learning applications with MIP solvers, and vice versa.

📬 Contact

office
Room 3024 at ZIB
e-mail

🎓 Curriculum vitae

since 2020
Researcher at ZIB
May 2020
M.Sc. in Mathematics in Finance and Industry at TU Braunschweig
Mar 2017
B.Sc. in Mathematics in Finance and Industry at TU Braunschweig

đź“ť Publications and preprints

Preprints

  1. Bolusani, S., Besançon, M., Bestuzheva, K., Chmiela, A., Dionísio, 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]
    @techreport{BolusaniEtal2024,
      year = {2024},
      institution = {Zuse Institute Berlin},
      type = {ZIB Report},
      month = feb,
      number = {24-02-29},
      url = {https://nbn-resolving.org/urn:nbn:de:0297-zib-95528},
      archiveprefix = {arXiv},
      eprint = {2402.17702},
      primaryclass = {math.OC},
      author = {Bolusani, Suresh and Besançon, Mathieu and Bestuzheva, Ksenia and Chmiela, Antonia and Dionísio, João and Donkiewicz, Tim and van Doornmalen, Jasper and Eifler, Leon and Ghannam, Mohammed and Gleixner, Ambros and Graczyk, Christoph and Halbig, Katrin and Hedtke, Ivo and Hoen, Alexander and Hojny, Christopher and van der Hulst, Rolf and Kamp, Dominik and Koch, Thorsten and Kofler, Kevin and Lentz, Jurgen and Manns, Julian and Mexi, Gioni and Mühmer, Erik and Pfetsch, Marc and Schlösser, Franziska and Serrano, Felipe and Shinano, Yuji and Turner, Mark and Vigerske, Stefan and Weninger, Dieter and Xu, Liding},
      title = {The SCIP Optimization Suite 9.0},
      code = {https://scipopt.org}
    }
  2. 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] [code]
    [BibTeX]
    @techreport{BestuzhevaBesanconEtal2021,
      year = {2021},
      institution = {Zuse Institute Berlin},
      type = {ZIB Report},
      month = dec,
      number = {21-41},
      url = {https://nbn-resolving.org/urn:nbn:de:0297-zib-85309},
      author = {Bestuzheva, Ksenia and Besançon, Mathieu and Chen, Wei-Kun and Chmiela, Antonia and Donkiewicz, Tim and van Doornmalen, Jasper and Eifler, Leon and Gaul, Oliver and Gamrath, Gerald and Gleixner, Ambros and Gottwald, Leona and Graczyk, Christoph and Halbig, Katrin and Hoen, Alexander and Hojny, Christopher and van der Hulst, Rolf and Koch, Thorsten and Lübbecke, Marco and Maher, Stephen J. and Matter, Frederic and Mühmer, Erik and Müller, Benjamin and Pfetsch, Marc and Rehfeldt, Daniel and Schlein, Steffan and Schlösser, Franziska and Serrano, Felipe and Shinano, Yuji and Sofranac, Boro and Turner, Mark and Vigerske, Stefan and Wegscheider, Fabian and Wellner, Philipp and Weninger, Dieter and Witzig, Jakob},
      title = {The SCIP Optimization Suite 8.0},
      code = {https://scipopt.org}
    }

Full articles

  1. 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]
    @article{BestuzhevaBesanconEtal2023,
      year = {2023},
      journal = {ACM Transactions on Mathematical Software},
      doi = {10.1145/3585516},
      archiveprefix = {arXiv},
      eprint = {2303.07101},
      primaryclass = {math.OC},
      author = {Bestuzheva, Ksenia and Besançon, Mathieu and Chen, Wei-Kun and Chmiela, Antonia and Donkiewicz, Tim and van Doornmalen, Jasper and Eifler, Leon and Gaul, Oliver and Gamrath, Gerald and Gleixner, Ambros and Gottwald, Leona and Graczyk, Christoph and Halbig, Katrin and Hoen, Alexander and Hojny, Christopher and van der Hulst, Rolf and Koch, Thorsten and Lübbecke, Marco and Maher, Stephen J. and Matter, Frederic and Mühmer, Erik and Müller, Benjamin and Pfetsch, Marc and Rehfeldt, Daniel and Schlein, Steffan and Schlösser, Franziska and Serrano, Felipe and Shinano, Yuji and Sofranac, Boro and Turner, Mark and Vigerske, Stefan and Wegscheider, Fabian and Wellner, Philipp and Weninger, Dieter and Witzig, Jakob},
      title = {Enabling Research Through the SCIP Optimization Suite 8.0}
    }

🔬 Projects

MiniMIP: a Faster, More Reliable, and Easier Way to Maintain and Solve MIP Problems

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.

miniMIP
Jan 2021 to Dec 2023
2

Adaptive Algorithms Through Machine Learning: Exploiting Interactions in Integer Programming

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.

MATH+ EF1-9
Jan 2021 to Dec 2022
5
3

đź’¬ Talks and posters

Conference and workshop talks

Nov 2022
Orthogonality-based Cut Selection
SCIP Workshop, Berlin
Oct 2022
Orthogonality-based Cut Selection
INFORMS Conference, Indianapolis

Poster presentations

Mar 2023
Workshop on Optimization and Machine Learning, Waischenfeld
Oct 2022
Learning Primal Heuristics and Cut Selection in MIPs
MATH+ Day, Berlin