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Department of Data Science

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Department of Data Science

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  4. Analytics & Mixed-Integer Optimization
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  6. Dr. Andreas Bärmann
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Publications

Publications

2023

  • Aigner KM., Bärmann A., Braun K., Liers F., Pokutta S., Schneider O., Sharma K., Tschuppik S.:
    Distributionally Robust Optimization over Time
    (2023)
    URL: https://opus4.kobv.de/opus4-trr154/frontdoor/index/index/docId/496
  • Bärmann A., Gemander P., Merkert M., Wiertz AK., Zaragoza Martínez FJ.:
    Algorithms for the clique problem with multiple-choice constraints under a series–parallel dependency graph
    In: Discrete Applied Mathematics 324 (2023), p. 145-166
    ISSN: 0166-218X
    DOI: 10.1016/j.dam.2022.09.015
  • Bärmann A., Martin A., Staszek J.:
    A decomposition approach for integrated locomotive scheduling and driver rostering in rail freight transport
    (2023)
    URL: http://www.optimization-online.org/DB_HTML/2021/08/8571.html
  • Hager L., Bärmann A., Burlacu R., Hildebrand R., Beach B.:
    Enhancements of Discretization Approaches for Non-Convex Mixed-Integer Quadratically Constraint Quadratic Programming
    (2023)
  • Wagner F., Bärmann A., Liers F., Weissenbäck M.:
    Improving Quantum Computation by Optimized Qubit Routing
    (2023)
    URL: https://arxiv.org/pdf/2206.01294.pdf

2022

  • Bärmann A., Burlacu R., Hager L., Kleinert T.:
    On Piecewise Linear Approximations of Bilinear Terms: Structural Comparison of Univariate and Bivariate Mixed-Integer Programming Formulations
    In: Journal of Global Optimization (2022)
    ISSN: 0925-5001
    Open Access: https://link.springer.com/article/10.1007/s10898-022-01243-y
    URL: http://www.optimization-online.org/DB_HTML/2021/08/8536.html
  • Bärmann A., Gemander P., Hager L., Noeth F., Schneider O.:
    EETTlib-Energy-efficient train timetabling library
    In: Networks (2022)
    ISSN: 0028-3045
    DOI: 10.1002/net.22117
  • Bärmann A., Gemander P., Martin A., Merkert M.:
    On Recognizing Staircase Compatibility
    In: Journal of Optimization Theory and Applications (2022)
    ISSN: 0022-3239
    DOI: 10.1007/s10957-022-02091-2

2021

  • Bärmann A., Martin A., Schneider O.:
    Efficient Formulations and Decomposition Approaches for Power Peak Reduction in Railway Traffic via Timetabling
    In: Transportation Science 55 (2021), p. 747-767
    ISSN: 0041-1655
    DOI: 10.1287/trsc.2020.1021
  • Bärmann A., Schneider O.:
    Set characterizations and convex extensions for geometric convex-hull proofs
    In: Mathematical Programming (2021)
    ISSN: 1436-4646
    DOI: 10.1007/s10107-021-01705-3
  • Roeder G., Ott L., Maier A., Wunder B., Wienzek P., Bärmann A., Liers F., Schellenberger M.:
    Analysis and Improvement of LVDC-Grid Stability using Circuit Simulation and Machine Learning - A Case Study
    NEIS 2021 Conference on Sustainable Energy Supply
    and Energy Storage Systems
    (Hamburg, 13. September 2021 - 14. September 2021)

2020

  • Bärmann A., Gemander P., Merkert M.:
    The clique problem with multiple-choice constraints under a cycle-free dependency graph
    In: Discrete Applied Mathematics (2020)
    ISSN: 0166-218X
    DOI: 10.1016/j.dam.2019.12.015

2019

  • Bärmann A., Büsing C., Liers F.:
    Globalized Robust Optimization with Gamma-Uncertainties
    (2019)
    URL: http://www.optimization-online.org/DB_HTML/2019/06/7253.html
    (Techreport)

2018

  • Bärmann A.:
    An Optimal Expansion Strategy for the German Railway Network Until 2030
    In: Fink A, Fügenschuh A, Geiger MJ (ed.): Operations Research Proceedings 2016, Cham: 2018
  • Bärmann A., Gellermann T., Merkert M., Schneider O.:
    Staircase Compatibility and its Applications in Scheduling and Piecewise Linearization
    In: Discrete Optimization 29 (2018), p. 111-132
    ISSN: 1572-5286
    DOI: 10.1016/j.disopt.2018.04.001
    URL: http://www.sciencedirect.com/science/article/pii/S1572528618300306
  • Bärmann A., Liers F.:
    Aggregation Methods for Railway Network Design Based on Lifted Benders Cuts
    In: Borndörfer R, Klug T, Lamorgese L, Mannino C, Reuther M, Schlechte T (ed.): Handbook of Optimization in the Railway Industry, Cham: Springer International Publishing, 2018, p. 47--72
    ISBN: 978-3-319-72153-8

    DOI: 10.1007/978-3-319-72153-8_3

2017

  • Bärmann A., Heidt A., Martin A., Pokutta S., Thurner C.:
    Erratum to: Polyhedral approximation of ellipsoidal uncertainty sets via extended formulations: a computational case study (Computational Management Science, (2016), 13, 2, (151-193), 10.1007/s10287-015-0243-0)
    In: Computational Management Science 14 (2017), p. 293-296
    ISSN: 1619-697X
    DOI: 10.1007/s10287-016-0269-y
  • Bärmann A., Martin A., Schneider O.:
    A comparison of performance metrics for balancing the power consumption of trains in a railway network by slight timetable adaptation
    In: Public Transport 9 (2017), p. 95-113
    ISSN: 1613-7159
    DOI: 10.1007/s12469-017-0160-4
  • Bärmann A., Martin A., Schuelldorf H.:
    A Decomposition Method for Multiperiod Railway Network Expansion - With a Case Study for Germany
    In: Transportation Science (2017)
    ISSN: 0041-1655
    DOI: 10.1287/trsc.2017.0747
  • Bärmann A., Pokutta S., Schneider O.:
    Emulating the Expert: Inverse Optimization through Online Learning
    In: Precup D, Teh YW (ed.): Proceedings of the 34th International Conference on Machine Learning (ICML), International Convention Centre, Sydney, Australia: 2017
    URL: http://proceedings.mlr.press/v70/barmann17a.html

2015

  • Bärmann A., Heidt A., Martin A., Pokutta S., Thurner C.:
    Polyhedral approximation of ellipsoidal uncertainty sets via extended formulations: a computational case study
    In: Computational Management Science 13 (2015), p. 151-193
    ISSN: 1619-697X
    DOI: 10.1007/s10287-015-0243-0
  • Bärmann A., Liers F., Martin A., Merkert M., Thurner C., Weninger D.:
    Solving Network Design Problems via Iterative Aggregation
    In: Mathematical Programming Computation 7 (2015), p. 189-217
    ISSN: 1867-2957
    DOI: 10.1007/s12532-015-0079-1

 

Department of Data Science
Friedrich-Alexander-Universität Erlangen-Nürnberg

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