Combinatorial Optimization under Uncertainty
Seminar for Bachelor and Master Students
|Date:||October 7, 2015|
TopicsThe 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.
PrerequisitesParticipants 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 datesA 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.
ScheduleWe 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|