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Sven Jäger

Lupe [1]

Wissenschaftlicher Mitarbeiter

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

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

E-Mail: jaeger #at# math.tu-berlin.de [2]
Tel.: +49 (0)30 314-21095
Fax: +49 (0)30 314-25191
Raum: MA 511
Sprechzeiten: Dienstag 17:00 Uhr. Bitte schicken Sie mir bis Dienstagmittag eine E-Mail, um den Zoom-Link zu erhalten.

Forschungsinteressen

  • Approximationsalgorithmen
  • Scheduling
  • Symmetrische Kettenzerlegungen

Lehre

Assistenzen
SS 2021
Computerorientierte Mathematik II [3] (theoretische Hausaufgaben)
WS 2020/21
Introduction to Linear and Combinatorial Optimization (ADM I)
SS 2020
Discrete Optimization (ADM II) [4]
WS 2019/20
Introduction to Linear and Combinatorial Optimization (ADM I) [5]
SS 2019
Discrete Optimization (ADM II) [6]
WS 2018/19
Introduction to Linear and Combinatorial Optimization (ADM I) [7]
SS 2018
Computerorientierte Mathematik II [8] (Programmieraufgaben)
WS 2017/18
Computerorientierte Mathematik I [9] (Programmieraufgaben)
SS 2017
Computerorientierte Mathematik II [10] (theoretische Hausaufgaben)
WS 2016/17
Computerorientierte Mathematik I [11] (theoretische Hausaufgaben)

Lebenslauf

Seit Juli 2016
Wissenschaftlicher Mitarbeiter am Lehrstuhl von Martin Skutella [12], Technische Universität Berlin
2013 - 2016:
Masterstudium der Mathematik und der Angewandten Informatik an der Georg-August-Universität Göttingen [13]
2010 - 2013:
Bachelor-Studium der Mathematik und der Angewandten Informatik an der Georg-August-Universität Göttingen [14]
2010:
Abitur am Hainberg-Gymnasium Göttingen [15]

Veröffentlichungen

The blockwise coordinate descent method for integer programs
Zitatschlüssel JaegerSchoebel2019
Autor Jäger, Sven and Schöbel, Anita
Seiten 357–381
Jahr 2019
ISSN 1432-5217
DOI 10.1007/s00186-019-00673-x
Journal Mathematical Methods of Operations Research
Jahrgang 91
Monat June
Zusammenfassung 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 zur Publikation [16] Link zur Originalpublikation [17] Download Bibtex Eintrag [18]
The blockwise coordinate descent method for integer programs [20]
Zitatschlüssel JaegerSchoebel2019
Autor Jäger, Sven and Schöbel, Anita
Seiten 357–381
Jahr 2019
ISSN 1432-5217
DOI 10.1007/s00186-019-00673-x
Journal Mathematical Methods of Operations Research
Jahrgang 91
Monat June
Zusammenfassung 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 zur Publikation [21] Link zur Originalpublikation [22] Download Bibtex Eintrag [23]
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