On Stability in Optimistic Bilevel Optimization
Optimization and Control
2025-02-25 v2 Machine Learning
Systems and Control
Systems and Control
Abstract
Solutions of bilevel optimization problems tend to suffer from instability under changes to problem data. In the optimistic setting, we construct a lifted formulation that exhibits desirable stability properties under mild assumptions that neither invoke convexity nor smoothness. The upper- and lower-level problems might involve integer restrictions and disjunctive constraints. In a range of results, we invoke at most pointwise and local calmness for the lower-level problem in a sense that holds broadly. The lifted formulation is computationally attractive with structural properties being brought out and an outer approximation algorithm becoming available.
Cite
@article{arxiv.2408.13323,
title = {On Stability in Optimistic Bilevel Optimization},
author = {Johannes O. Royset},
journal= {arXiv preprint arXiv:2408.13323},
year = {2025}
}