Geometric and computational hardness of bilevel programming
<|reference_start|>Geometric and computational hardness of bilevel programming: We first show a simple but striking result in bilevel optimization: unconstrained $C^\infty$ smooth bilevel programming is as hard as general extended-real-valued lower semicontinuous minimization. We then proceed to a worst-case analysis of box-constrained bilevel polynomial optimization. We show in particular that any extended-real-valued semi-algebraic function, possibly non-continuous, can be expressed as the value function of a polynomial bilevel program. Secondly, from a computational complexity perspective, the decision version of polynomial bilevel programming is one level above NP in the polynomial hierarchy ($\Sigma^p_2$-hard). Both types of difficulties are uncommon in non-linear programs for which objective functions are typically continuous and belong to the class NP. These results highlight the irremediable hardness attached to general bilevel optimization and the necessity of imposing some form of regularity on the lower level.<|reference_end|>
@article{bolte2024geometric,
    title={Geometric and computational hardness of bilevel programming},
    author={J'er^ome Bolte (TSE-R), Quoc-Tung Le (TSE-R), Edouard Pauwels
  (LAAS-MAC, IRIT-ADRIA, TSE-R), Samuel Vaiter (CNRS, LJAD)},
    journal={arXiv preprint arXiv:2407.12372},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.12372},
    primaryClass={cs.CC math.OC}
}