Polynomial calculus for optimization

Abstract

MaxSAT is the problem of finding an assignment satisfying the maximum number of clauses in a CNF formula. We consider a natural generalization of this problem to generic sets of polynomials and propose a weighted version of Polynomial Calculus to address this problem.

Weighted Polynomial Calculus is a natural generalization of the systems MaxSAT-Resolution and weighted Resolution. Unlike such systems, weighted Polynomial Calculus manipulates polynomials with coefficients in a finite field and either weights in $N$ or $Z$. We show the soundness and completeness of weighted Polynomial Calculus via an algorithmic procedure.

Weighted Polynomial Calculus, with weights in $N$ and coefficients in $F_2$, is able to prove efficiently that Tseitin formulas on a connected graph are minimally unsatisfiable. Using weights in $Z$, it also proves efficiently that the Pigeonhole Principle is minimally unsatisfiable.