Antonia Chmiela

My research interests revolve around discrete optimization, machine learning and the intersection thereof. Specifically, I am interested in developing methods to solve mixed-integer (non-linear) programms more efficiently. To do so, I focus on the theoretical development of new cutting planes paradigmns and the practical application of offline and online techniques to improve the application of primal heuristics within a MIP solver.

📬 Contact

office
Room 3102 at ZIB
e-mail

🎓 Curriculum vitae

since 2020
Researcher at ZIB
2020
M.Sc. in Mathematics at TUB
2018
B.Sc. in Mathematics at TUB

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{2024_BolusaniEtAl_Scip9,
      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. Turner, M., Chmiela, A., Koch, T., and Winkler, M. (2023). PySCIPOpt-ML: Embedding Trained Machine Learning Models Into Mixed-integer Programs. [arXiv]
    [BibTeX]
    @misc{2023_TurnerChmielaKochMichael_Pyscipoptml,
      archiveprefix = {arXiv},
      eprint = {2312.08074},
      primaryclass = {math.OC},
      year = {2023},
      author = {Turner, Mark and Chmiela, Antonia and Koch, Thorsten and Winkler, Michael},
      title = {PySCIPOpt-ML: Embedding Trained Machine Learning Models Into Mixed-integer Programs}
    }
  3. 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{2021_BestuzhevaEtAl_Scip8,
      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}
    }

Conference proceedings

  1. Chmiela, A., Gleixner, A., Lichocki, P., and Pokutta, S. (2023). Online Learning for Scheduling MIP Heuristics. Proceedings of International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 114–123. DOI: 10.1007/978-3-031-33271-5_8
    [BibTeX]
    @inproceedings{2023_ChmielaGleixnerLichockiPokutta_Onlinelearningscheduling,
      year = {2023},
      booktitle = {Proceedings of International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research},
      pages = {114-123},
      doi = {10.1007/978-3-031-33271-5_8},
      author = {Chmiela, Antonia and Gleixner, Ambros and Lichocki, Pawel and Pokutta, Sebastian},
      title = {Online Learning for Scheduling MIP Heuristics}
    }
  2. Chmiela, A., Muñoz, G., and Serrano, F. (2023). Monoidal Strengthening and Unique Lifting in MIQCPs. Proceedings of Conference on Integer Programming and Combinatorial Optimization. [URL]
    [BibTeX]
    @inproceedings{2023_ChmielaMuozSerrano_Monoidalstrengthening,
      year = {2023},
      booktitle = {Proceedings of Conference on Integer Programming and Combinatorial Optimization},
      url = {https://gonzalomunoz.org/monoidalforMIQCP.pdf},
      author = {Chmiela, Antonia and Muñoz, Gonzalo and Serrano, Felipe},
      title = {Monoidal Strengthening and Unique Lifting in MIQCPs}
    }
  3. 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 Conference of the Society for Operations Research in Germany. [arXiv]
    [BibTeX]
    @inproceedings{2023_MexiEtAl_Scyllaheuristic,
      year = {2023},
      booktitle = {Proceedings of Conference of the Society for Operations Research in Germany},
      archiveprefix = {arXiv},
      eprint = {2307.03466},
      primaryclass = {math.OC},
      author = {Mexi, Gioni and Besançon, Mathieu and Bolusani, Suresh and Chmiela, Antonia and Hoen, Alexander and Gleixner, Ambros},
      title = {Scylla: a Matrix-free Fix-propagate-and-project Heuristic for Mixed-integer Optimization}
    }
  4. 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 Conference on Neural Information Processing Systems, 176, 220–231. [URL] [arXiv]
    [BibTeX]
    @inproceedings{2022_GasseEtAl_Ml4coinsights,
      year = {2022},
      booktitle = {Proceedings of Conference on Neural Information Processing Systems},
      month = jun,
      volume = {176},
      pages = {220–231},
      url = {https://proceedings.mlr.press/v176/gasse22a.html},
      archiveprefix = {arXiv},
      eprint = {2203.02433},
      primaryclass = {cs.LG},
      author = {Gasse, Maxime and Bowly, Simon and Cappart, Quentin and Charfreitag, Jonas and Charlin, Laurent and Chételat, Didier and Chmiela, Antonia and Dumouchelle, Justin and Gleixner, Ambros and Kazachkov, Aleksandr M. and Khalil, Elias and Lichocki, Pawel and Lodi, Andrea and Lubin, Miles and Maddison, Chris J. and Christopher, Morris and Papageorgiou, Dimitri J. and Parjadis, Augustin and Pokutta, Sebastian and Prouvost, Antoine and Scavuzzo, Lara and Zarpellon, Giulia and Yang, Linxin and Lai, Sha and Wang, Akang and Luo, Xiaodong and Zhou, Xiang and Huang, Haohan and Shao, Shengcheng and Zhu, Yuanming and Zhang, Dong and Quan, Tao and Cao, Zixuan and Xu, Yang and Huang, Zhewei and Zhou, Shuchang and Binbin, Chen and Minggui, He and Hao, Hao and Zhiyu, Zhang and Zhiwu, An and Kun, Mao},
      title = {The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights}
    }
  5. Chmiela, A., Khalil, E. B., Gleixner, A., Lodi, A., and Pokutta, S. (2021). Learning to Schedule Heuristics in Branch-and-bound. Proceedings of Conference on Neural Information Processing Systems, 34, 24235–24246. [URL] [arXiv] [poster]
    [BibTeX]
    @inproceedings{2021_ChmielaEtAl_Heuristicscheduling,
      year = {2021},
      booktitle = {Proceedings of Conference on Neural Information Processing Systems},
      month = mar,
      volume = {34},
      pages = {24235–24246},
      url = {https://proceedings.neurips.cc/paper_files/paper/2021/file/cb7c403aa312160380010ee3dd4bfc53-Paper.pdf},
      archiveprefix = {arXiv},
      eprint = {2103.10294},
      primaryclass = {cs.LG},
      author = {Chmiela, Antonia and Khalil, Elias B. and Gleixner, Ambros and Lodi, Andrea and Pokutta, Sebastian},
      title = {Learning to Schedule Heuristics in Branch-and-bound},
      poster = {https://pokutta.com/slides/20211120_poster_NeurIPS21_learningheuristics.pdf}
    }
  6. Chmiela, A., Muñoz, G., and Serrano, F. (2021). On the Implementation and Strengthening of Intersection Cuts for QCQPs. Proceedings of Integer Programming and Combinatorial Optimization: 22nd International Conference, IPCO 2021, 134–147. DOI: 10.1007/978-3-030-73879-2_10
    [BibTeX]
    @inproceedings{2022_ChmielaMuozSerrano_Intersectioncutsqcqps:1,
      year = {2021},
      booktitle = {Proceedings of Integer Programming and Combinatorial Optimization: 22nd International Conference, IPCO 2021},
      pages = {134-147},
      doi = {10.1007/978-3-030-73879-2_10},
      author = {Chmiela, Antonia and Muñoz, Gonzalo and Serrano, Felipe},
      title = {On the Implementation and Strengthening of Intersection Cuts for QCQPs}
    }

Full articles

  1. 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]
    @article{2023_BestuzhevaEtAl_GlobaloptimizationScip80,
      year = {2023},
      journal = {Journal of Global Optimization},
      doi = {10.1007/s10898-023-01345-1},
      note = {ZIB report 23-01},
      url = {https://nbn-resolving.org/urn:nbn:de:0297-zib-89348},
      archiveprefix = {arXiv},
      eprint = {2301.00587},
      primaryclass = {math.OC},
      author = {Bestuzheva, Ksenia and Chmiela, Antonia and MĂĽller, Benjamin and Serrano, Felipe and Vigerske, Stefan and Wegscheider, Fabian},
      title = {Global Optimization of Mixed-integer Nonlinear Programs with SCIP 8.0}
    }
  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. (2023). Enabling Research Through the SCIP Optimization Suite 8.0. ACM Transactions on Mathematical Software. DOI: 10.1145/3585516 [arXiv]
    [BibTeX]
    @article{2023_BestuzhevaEtAl_ResearchScip,
      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}
    }
  3. 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]
    @article{2022_ChmielaMuozSerrano_Intersectioncutsqcqps,
      year = {2022},
      journal = {Mathematical Programming B},
      volume = {197},
      pages = {549-586},
      doi = {10.1007/s10107-022-01808-5},
      author = {Chmiela, Antonia and Muñoz, Gonzalo and Serrano, Felipe},
      title = {On the Implementation and Strengthening of Intersection Cuts for QCQPs}
    }

🔬 Projects

Learning to Schedule Heuristics in IP

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.

HLEARN
Nov 2021 to Oct 2023
2
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

Jun 2023
24th IPCO Conference, Madison
May 2023
Online Learning for Scheduling MIP Heuristics
ZIB-Siemens Workshop, Munich
May 2023
20th CPAIOR Conference, Nice
Jan 2023
Online Learning for Scheduling MIP Heuristics
SAP-ZIB Workshop, Walldorf
Jan 2023
Combinatorial Optimization Workshop, Aussois
View More / Less
Nov 2022
SCIP Workshop, Berlin
Oct 2021
INFORMS Conference, Anaheim
Jul 2021
31st EURO Conference, Athens
May 2021
22nd IPCO Conference

Poster presentations

Feb 2023
Learning to Schedule MIP Heuristics
IPAM Workshop on Artificial Intelligence and Discrete Optimization, Los Angeles
May 2022
Monoidal Strengthening for Intersection Cuts Using Maximal Quadratic-Free Sets
MIP Workshop
Dec 2021
Learning to Schedule Heuristics in Branch-and-Bound
NeurIPS Conference
May 2021
Learning to Schedule Heuristics in Branch-and-Bound
MIP Workshop

👩‍🏫Teaching

summer 2023
Seminar Supervisor for Cutting Planes for Mixed-Integer Programming at TUB
winter 2017
Tutor for Mathematics for Chemists I at TUB
summer 2017
Tutor for Mathematics for Chemists II at TUB
winter 2016
Tutor for Mathematics for Chemists I at TUB