Title: On Robust Selection Problems
Speaker: Marc Goerigk
Affiliation: Department of Management Science – Lancaster University
Location: Room LT1 Business School
Time: 2:30pm (1 hour)

Abstract. Robust optimisation considers problems that are affected by uncertain data: How can we find a solution that performs well, even if things don’t go quite as planned? Typically, adding robustness to a problem makes it harder to solve. The selection problem is maybe the simplest non-trivial combinatorial optimisation problem. Given a set of n items, the task is to choose p items that maximise some profit. Being that simple, it is an interesting object of study for complexity in robust optimisation, as its robust counterparts sometimes turn out to become NP-hard, sometimes not. In this talk I present some of the complexity results in this area, which can be surprising. Along the way, we develop an overview on different approaches to robust optimisation, and see what they mean for the selection problem.

About the speaker. Marc Goerigk is a Lecturer in the Department of Management Science at Lancaster University. He studied mathematics and computer science at the University of Gottingen, where he also completed his PhD in applied mathematics in 2012. From 2012 to 2015, he worked as a Post-Doc at the University of Kaiserslautern. Besides robust optimisation, his research interests include disaster management and public transportation problems.