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Combinatorial Optimization under Uncertainty

Seminar for Bachelor and Master Students


Advisor: Nicole Megow
Date: October 7, 2015
ECTS credits: 3


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.

Important dates

A preparatory meeting where possible seminar topics etc. are presented will take place on Wednesday, July 1, 2015 at 6 pm in room MI 02.04.011.

This seminar will be held as a block seminar on Wednesday, October 7, 2015 in room MI 02.06.011.


We have the following (tentative) schedule.

09:00 Markus Kellerer: Online Dial-a-Ride
10:15 Malte Kriegelsteiner: The Stackelberg MST Game
11:30 Rosalia Marrobio: Knapsack with Cardinality Robustness

13:30 Daniel Schmidt gen. Waldschmidt: Thresholded Covering Algorithms
14:45 Edward Anderson: Stochastic Scheduling

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.