On the strength of recursive McCormick relaxations for binary polynomial optimization
Optimization and Control
2023-01-19 v2
Abstract
Recursive McCormick relaxations have been among the most popular convexification techniques for binary polynomial optimization problems. It is well-understood that both the quality and the size of these relaxations depend on the recursive sequence, and finding an optimal recursive sequence amounts to solving a difficult combinatorial optimization problem. In this paper, we prove that any recursive McCormick relaxation is implied by the extended flower relaxation, a linear programming relaxation that is a natural generalization of the flower relaxation introduced by Del Pia and Khajavirad 2018, which for binary polynomial optimization problems with fixed degree can be solved in strongly polynomial time.
Cite
@article{arxiv.2209.13034,
title = {On the strength of recursive McCormick relaxations for binary polynomial optimization},
author = {Aida Khajavirad},
journal= {arXiv preprint arXiv:2209.13034},
year = {2023}
}