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TU Berlin

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Sven Jäger

Lupe

Research assistant

Fakultät II - Mathematik und Naturwissenschaften
Institut für Mathematik, Sekr. MA 5-2

Technische Universität Berlin
Straße des 17. Juni 136
10623 Berlin
Germany

E-Mail:
Tel.: +49 (0)30 314-21095
Fax: +49 (0)30 314-25191
Room: MA 511
Consultation hours: Tuesday 5:00 pm. Please send me an email before Tuesday noon in order to get the zoom link.

Research interests

  • Apprroximation algorithms
  • Scheduling
  • Symmetric Chain Decompositions

Teaching

Assistances
Summer 2021
Computerorientierte Mathematik II (theoretical exercises)
Winter 2020/21
Introduction to Linear and Combinatorial Optimization (ADM I)
Summer 2020
Discrete Optimization (ADM II)
Winter 2019/20
Introduction to Linear and Combinatorial Optimization (ADM I)
Summer 2019
Discrete Optimization (ADM II)
Winter 2018/19
Introduction to Linear and Combinatorial Optimization (ADM I)
Summer 2018
Computerorientierte Mathematik II (programming exercises)
Winter 2017/18
Computerorientierte Mathematik I (programming exercises)
Summer 2017
Computerorientierte Mathematik II (theoretical exercises)
Winter 2016/17
Computerorientierte Mathematik I (theoretical exercises)

Curriculum Vitae

Since July 2016
Doctoral student with Martin Skutella, Technische Universität Berlin
2013 - 2016:
Master studies in Mathematics and in Applied Computer Science at Georg-August-Universität Göttingen, Germany.
2010 - 2013:
Bachelor studies in Mathematics and in Applied Computer Science at Georg-August-Universität Göttingen, Germany.
2010:
Abitur at Hainberg-Gymnasium Göttingen

Publications

The blockwise coordinate descent method for integer programs
Citation key JaegerSchoebel2019
Author Jäger, Sven and Schöbel, Anita
Pages 357–381
Year 2019
ISSN 1432-5217
DOI 10.1007/s00186-019-00673-x
Journal Mathematical Methods of Operations Research
Volume 91
Month June
Abstract Blockwise coordinate descent methods have a long tradition in continuous optimization and are also frequently used in discrete optimization under various names. New interest in blockwise coordinate descent methods arises for improving sequential solutions for problems which consist of several planning stages. In this paper we systematically formulate and analyze the blockwise coordinate descent method for integer programming problems. We discuss convergence of the method and properties of the resulting solutions. We extend the notion of Pareto optimality for blockwise coordinate descent to the case that the blocks do not form a partition and compare Pareto optimal solutions to blockwise optimal and to global optimal solutions. Among others we derive a condition which ensures that the solution obtained by blockwise coordinate descent is weakly Pareto optimal and we confirm convergence of the blockwise coordinate descent to a global optimum in matroid polytopes. The results are interpreted in the context of multi-stage linear integer programming problems and illustrated for integrated planning in public transportation.
Link to publication Link to original publication Download Bibtex entry
The blockwise coordinate descent method for integer programs
Citation key JaegerSchoebel2019
Author Jäger, Sven and Schöbel, Anita
Pages 357–381
Year 2019
ISSN 1432-5217
DOI 10.1007/s00186-019-00673-x
Journal Mathematical Methods of Operations Research
Volume 91
Month June
Abstract Blockwise coordinate descent methods have a long tradition in continuous optimization and are also frequently used in discrete optimization under various names. New interest in blockwise coordinate descent methods arises for improving sequential solutions for problems which consist of several planning stages. In this paper we systematically formulate and analyze the blockwise coordinate descent method for integer programming problems. We discuss convergence of the method and properties of the resulting solutions. We extend the notion of Pareto optimality for blockwise coordinate descent to the case that the blocks do not form a partition and compare Pareto optimal solutions to blockwise optimal and to global optimal solutions. Among others we derive a condition which ensures that the solution obtained by blockwise coordinate descent is weakly Pareto optimal and we confirm convergence of the blockwise coordinate descent to a global optimum in matroid polytopes. The results are interpreted in the context of multi-stage linear integer programming problems and illustrated for integrated planning in public transportation.
Link to publication Link to original publication Download Bibtex entry

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