Bilevel Optimization Under Uncertainty: Challenges and Opportunities

Département Information Systems et Operations Management

Intervenant: Ivana Ljubic (ESSEC)

Salle Bernard Ramanantsoa

Abstract

Thanks to significant algorithmic advances in the field of computational bilevel optimization, today we can solve much larger and more complicated bilevel problems compared to what was possible two decades ago. In this talk, we will focus on one of the emerging and challenging classes of bilevel problems: bilevel optimization under uncertainty. We will discuss classical ways of addressing uncertainties in bilevel optimization using stochastic or robust optimization techniques. However, the sources of uncertainty in bilevel optimization can be much richer than for usual, single-level problems, since not only the problem’s data can be uncertain but also the (observation of the) decisions of the two players can be subject to uncertainty. Thus, we will also discuss bilevel optimization under limited observability, the area of problems considering only near-optimal decisions, and intermediate solution concepts between the optimistic and pessimistic cases.