The exact solution of bilevel optimization problems is a very challenging task that received more and more attention in recent years, as witnessed by the flourishing recent literature on this topic. In this paper we present ideas and algorithms to solve to proven optimality generic Mixed-Integer Bilevel Linear Programs (MIBLP’s) where all constraints are linear, and some/all variables are required to take integer values.
In doing so, we look for a general-purpose approach applicable to any MIBLP (under mild conditions), rather than ad-hoc methods for specific cases. Our approach concentrates on minimal additions required to convert an effective branch-and-cut MILP exact code into a valid MIBLP solver, thus inheriting the wide arsenal of MILP tools (cuts, branching rules, heuristics) available in modern solvers.
FISCHETTI, M., LJUBIC, I., MONACI, M. et SINNL, M. (2016). Intersection Cuts for Bilevel Optimization. Dans: Integer Programming and Combinatorial Optimization. 1st ed. Berlin: Springer Computer Science, pp. 77-88.