Discrete Optimization with Uncertainty
Course description: Many planning problems require knowledge about the future, which is difficult to predict. As a consequence, uncertainties are unavoidable. One way to deal with such uncertainties is robust optimization: a robust solution remains feasible as long as the input parameters belong to a predefined uncertainty set. In this mini-course, we learn how to robustify optimization problems, discuss different uncertainty sets with their pro and cons, and explore the robust counterpart of a number of (basic) discrete optimization problems. Moreover, extensions of the approach are considered alongside real-life applications.
Lecturer and Examiner
Professor Arie Koster, RWTH Aachen University, Germany.
- Monday 26 February 10.15-11.45, ITC 1245
- Tuesday 27 February 9.15-12.45, ITC 2345
- Wednesday 28 February 9.15-12.45, ITC 2345
- Thursday 1 March 9.15-12.45, ITC 1213
The lecture slides are available here.
Development of a research proposal, identifying research topics/problems of relevance and presenting the application of the knowledge gained from the course and own reading. (Proposed number of) ECTS Credits: 2.
Please contact Di Yuan if you have questions about this course.
The course has been sponsed by the Applied Optimisation Research Arena of the IT department of Uppsala University.