On the Computational Complexity of Bilevel Integer Linear Programming

We investigate the computational complexity of bilevel integer linear programming.

While Jeroslow~(1985) established that the decision version of this problem is $\Sigma^p_2$-complete when restricted to binary variables, we prove that this $\Sigma^p_2$-completeness persists even for general integer variables, settling a question that remained open for over 40 years.

Furthermore, we analyze the impact of various structural assumptions on computational complexity.

Notably, we strengthen the result of Köppe et al.~(2010) by proving polynomial-time solvability whenever the total number of upper- and lower-level variables is fixed, without any additional assumptions.