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Combinatorial Optimization under Uncertainty

Seminar for Bachelor and Master Students


Advisor: Nicole Megow
ECTS credits: 3
Time & Room Wed 12-14 in 02.04.011


The theory of combinatorial optimization provides powerful tools for modeling, understanding, and solving optimization problems that arise in all kinds of applications. A characteristic feature of many real-world applications is a certain degree of uncertainty regarding the problem data. Such uncertain problem data may be stochastic parameters or incrementally revealed online information.

The purpose of this seminar is to read and understand recent results from the literature on combinatorial optimization under uncertainty and related topics. This includes topics from online optimization, stochastic optimization and robustness models.


Participants are expected to have good knowledge of standard techniques and algorithms in the area of linear and combinatorial optimization. Ideally, they participated in the courses combinatorial Optimization MA4502 and/or Discrete Optimization MA3502.


We have the following (tentative) schedule. We begin always at 12:30.

14.10.15   Kick-Off Meeting: 5-minute presentations
28.10.15   Online Dial-a-Ride: Lucian Riediger
04.11.15   Robust Randomized Matchings: Michael Heptner
11.11.15   Stochastic Scheduling I: Martin Sperr
18.11.15   Robust Network Flows: Dominik Bruckner
25.11.15   Stochastic Scheduling II: Lukáš Folwarczný
09.12.15   Online Replacement Path Problem: Veronika Kreuzer
16.12.15   Stochastic Knapsack: Jonathan Roth
20.01.16   Online Appointment Scheduling: Raphael Ullmann
27.01.16   cancelled

Research Unit M9

Department of Mathematics
Boltzmannstraße 3
85748 Garching b. München
phone:+49 89 289-16858
fax:+49 089 289-16859


Prof. Dr. Peter Gritzmann
Applied Geometry and Discrete Mathematics

Prof. Dr. Andreas S. Schulz
Mathematics of Operations Research
(affiliated member of M9)

Prof. Dr. Stefan Weltge
Discrete Mathematics


Jan 25th, 2019
Case Studies 2019: Preliminary Meeting on Wed, Feb 6th, at 16:00 in room MI 03.06.011.