Relaxation strength for multilinear optimization: McCormick strikes back
Optimization and Control
2026-04-09 v3 Discrete Mathematics
Combinatorics
Abstract
We consider linear relaxations for multilinear optimization problems. In a recent paper, Khajavirad proved that the extended flower relaxation is at least as strong as the relaxation of any recursive McCormick linearization (Operations Research Letters 51 (2023) 146-152). In this paper we extend the result to more general linearizations, and present a simpler proof. Moreover, we complement Khajavirad's result by showing that the intersection of the relaxations of such linearizations and the extended flower relaxation are equally strong.
Cite
@article{arxiv.2311.08570,
title = {Relaxation strength for multilinear optimization: McCormick strikes back},
author = {Emily Schutte and Matthias Walter},
journal= {arXiv preprint arXiv:2311.08570},
year = {2026}
}
Comments
10 pages, 4 figures