Beyond hypergraph acyclicity: limits of tractability for pseudo-Boolean optimization

TL;DR

This paper explores the computational limits of pseudo-Boolean optimization on hypergraphs, establishing intractability results based on hypergraph properties and introducing a new measure that enables efficient solutions when certain conditions are met.

Contribution

It provides the first intractability results for pseudo-Boolean optimization on signed hypergraphs and introduces the nest-set gap, a new hypergraph measure for tractability analysis.

Findings

Intractability grows super-polynomially with treewidth for bounded rank hypergraphs.

Hypergraphs with bounded rank can have exponential extension complexity.

Bounded nest-set gap allows polynomial-size extended formulations and efficient algorithms.

Abstract

In this paper, we study the problem of minimizing a polynomial function with literals over all binary points, often referred to as pseudo-Boolean optimization. We investigate the fundamental limits of computation for this problem by providing new necessary conditions and sufficient conditions for tractability. On the one hand, we obtain the first intractability results, in the best-case sense, for pseudo-Boolean optimization problems on signed hypergraphs with bounded rank, in terms of the treewidth of the intersection graph. Namely, first, under some mild assumptions, we show that for every sequence of hypergraphs indexed by the treewidth and with bounded rank, the complexity of solving the associated pseudo-Boolean optimization problem grows super-polynomially in the treewidth. Second, we show that any hypergraph of bounded rank is the underlying hypergraph of some signed hypergraph for which the corresponding pseudo-Boolean polytope has an exponential extension complexity in the treewidth. On the other hand, we introduce the nest-set gap, a new hypergraph-theoretic notion that enables us to define a notion of "distance" from the hypergaph acyclicity. We prove that if this distance is bounded, the pseudo-Boolean polytope admits a polynomial-size extended formulation. This in turn enables us to obtain a polynomial-time algorithm for a large class of pseudo-Boolean optimization problems whose underlying hypergraphs contain beta-cycles.