
Matteo Fischetti:
Bilevel Optimization
Abstract:
Bilevel Optimization is a very challenging framework where two players (with different objectives) compete for the definition of the final solution. In this talk, we will address a generic MixedInteger Bilevel Linear Program (MIBLP), i.e., a bilevel optimization problem where all objective functions and constraints are linear, and some/all variables are required to take integer values. We will describe a generalpurpose solution approach built on top of a (more familiar) MixedInteger Linear Programming (MILP) solver. We will first describe a minimal set of modifications needed to turn a standard MILP solver into an exact MIBLP solver. We will then describe classes of linear inequalities to be embedded in the branchandcut framework, some of which are intersection cuts based on feasiblefree convex sets. We will finally present a computational study on various classes of benchmark instances from the literature.
