Optimization Over the Boolean Hypercube Via Sums of Nonnegative Circuit Polynomials

Various key problems from theoretical computer science can be expressed as polynomial optimization problems over the boolean hypercube. One particularly successful way to prove complexity bounds for these types of problems is based on sums of squares (SOS) as nonnegativity certificates. In this article, we initiate optimization problems over the boolean hypercube via a recent, alternative certificate called sums of nonnegative circuit polynomials (SONC). We show that key results for SOS-based certificates remain valid: First, for polynomials, which are nonnegative over the n-variate boolean hypercube with constraints of degree d there exists a SONC certificate of degree at most $$n+d$$ n + d . Second, if there exists a degree d SONC certificate for nonnegativity of a polynomial over the boolean hypercube, then there also exists a short degree d SONC certificate that includes at most $$n^{O(d)}$$ n O ( d ) nonnegative circuit polynomials. Moreover, we prove that, in opposite to SOS, the SONC cone is not closed under taking affine transformation of variables and that for SONC there does not exist an equivalent to Putinar’s Positivstellensatz for SOS. We discuss these results from both the algebraic and the optimization perspective.

Algorithmization and Software Implementation of the Method of Eliminating Variables in Polynomial Optimization Problems

The method of sequential exclusion of variables in polynomial optimization problems is considered. A number of problems are solved using this method. The practical steps of an algorithm are described, which reduces the initial polynomial optimization problem to a multi-stage branching process of obtaining a finite number of alternative problems, the output of which gives a finite set of polynomials in one variable. As a result, solving a number of polynomial problems reduces to sorting out a finite number of vectors whose components are the real roots of polynomials.