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Department of Data Science

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Department of Data Science

In page navigation: Research
  • Agile Teams
    • IBO – Intelligent Business Optimization
  • Research Groups
    • Analytics & Mixed-Integer Optimization
      • Group members
        • Dr. Andreas Bärmann
          • Projects
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        • M.Sc. Kristin Braun
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        • M.Sc. Adrian Göß
        • M.Sc. Lukas Hager
        • M.Sc. Johannes Hahn
        • M.Sc. Katrin Halbig
        • M.Sc. Jan Krause
        • M.Sc. Richard Krug
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        • Dipl.-Math. Galina Orlinskaya
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        • Dr. Jan Rolfes, Akad. Rat
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        • M.Sc. Sonja Weiland
        • Dr. Dieter Weninger, Akad. Rat
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    • Data Analytics
      • Prof. Dr. Timm Oertel
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      • Group members
        • M.Sc. Kevin-Martin Aigner
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        • M.Sc. Daniela Bernhard
        • M.Sc. Jana Dienstbier
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        • M.Sc. Benno Hoch
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        • M.Sc. Martina Kuchlbauer
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        • Prof. Dr. Frauke Liers
        • M.Sc. Florian Rösel
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        • Sebastian Tschuppik
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  • Professors, Lecturers and Researchers
    • Marie-Christine Düker
    • Jens Habermann
    • Johannes Helbig
    • Manfred Kronz
    • Frauke Liers
    • Timm Oertel
    • Dieter Weninger
    • Marius Yamakou
  • Secondary Members of DDS
    • Freimut Bodendorf
    • Günter Leugering
  • Former Members

M.Sc. Katrin Halbig

M.Sc. Katrin Halbig

Department of Data Science (DDS)
Chair of Analytics & Mixed-Integer Optimization

Room: Room 03.376
Cauerstraße 11
91058 Erlangen
  • Phone number: +49 9131 85-67179
  • Email: katrin.halbig@fau.de
  • Website: https://www.datascience.nat.fau.eu/research/groups/amio/members/katrin-halbig/

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  • Projects
  • Publications

Projects

  • Development of new Linear and Integer Programming Techniques to solve Supply Chain Management Problems


    (Third Party Funds Single)
    Term: since 1. March 2010
    Funding source: Industrie
    Abstract

    Supply Chain Management (SCM) deals with the combination of procurement, production, storage, transport and delivery of commodities. Problems of this kind occur in all kinds of industry branches. Since the integrated planning of these processes contains a high potential for optimization it is of great importance for the companies’ efficiency.

    The method of choice to find optimal solutions in SCM is linear and integer programming. Nevertheless, there are big challenges to overcome – concerning both hardware and algorithms – due to very detailed and therefore large models. Additionally there may occur numerical difficulties that standard techniques cannot deal with.

    As a consequence, the problem’s mathematical formulation has to be done carefully and new methods need to be implemented to improve the performance of MIP algorithms.

    →More information

Publications

2021

  • Bestuzheva K., Besançon M., Chen WK., 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 SJ., Matter F., Mühmer E., Müller B., Pfetsch ME., Rehfeldt D., Schlein S., Schlösser F., Serrano F., Shinano Y., Sofranac B., Turner M., Vigerske S., Wegscheider F., Wellner P., Weninger D., Witzig J.:
    The SCIP Optimization Suite 8.0
    (2021)
    (Techreport)
  • Halbig K., Hümbs L., Rösel F., Schewe L., Weninger D.:
    Computing optimality certificates for convex mixed-integer nonlinear problems
    (2021)
    URL: https://opus4.kobv.de/opus4-trr154/frontdoor/index/index/docId/476/
    (Techreport)

2020

  • Gamrath G., Anderson D., Bestuzheva K., Chen WK., Eifler L., Gasse M., Gemander P., Gleixner A., Gottwald L., Halbig K., Hendel G., Hojny C., Koch T., Le Bodic P., Maher SJ., Matter F., Miltenberger M., Mühmer E., Müller B., Pfetsch ME., Schlösser F., Serrano F., Shinano Y., Tawfik C., Vigerske S., Wegscheider F., Weninger D., Witzig J.:
    The SCIP Optimization Suite 7.0
    In: Konrad-Zuse-Zentrum für Informationstechnik Berlin : ZIB-Report (2020)
    (Techreport)

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

Cauerstr. 11
91058 Erlangen
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