Papers › Relaxations for binary polynomial optimization via signed certificates

Relaxations for binary polynomial optimization via signed certificates

22 May 2024arXiv:2405.13447links table onlyarchive 2025-07-28

Liding Xu, Leo Liberti

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We consider the problem of minimizing a polynomial f over the (binary) hypercube. We show that, for a specific set of polynomials, their binary non-negativity (i.e. on the hypercube) can be checked in polynomial time via minimum cut algorithms, from which we construct a linear programming representation for this set of polynomials. We categorize binary polynomials according to their signed support patterns and develop parameterized linear programming representations for binary non-negative polynomials. This allows the construction of signed certificates of binary non-negativity with adjustable signed support patterns and representation complexities; and we propose a method for minimizing f by decomposing it as a sum of signed certificates. This method yields new hierarchies of linear programming relaxations for binary polynomial optimization. Moreover, since our decomposition depends only on the support of f, the new hierarchies are sparsity-preserving.

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