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Sven Jäger
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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: jaeger #at# math.tu-berlin.de
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.
Teaching
| 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
| 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. |
| 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. |
Talks
- Approximating Total Weighted Completion Time on Identical Parallel Machines with Precedence Constraints and Release Dates MAPSP 2019 PDF, 292 KB
- Generalizing the Kawaguchi-Kyan Bound to Stochastic Parallel Machine Scheduling COW 2018, STACS 2018, ISMP 2018, BMS-BGSMath Junior Meeting 2019, FRICO 2019 PDF, 232 KB
- Gray codes and symmetric chains ICALP 2018 PDF, 381 KB
- On orthogonal symmetric chain decompositions EUROCOMB 2019 PDF, 449 KB
- Scheduling Stochastic Jobs with Release Dates on a Single Machine Dagstuhl Seminar Scheduling 2020 PDF, 457 KB