Face Identification via Polyhedral Relaxations for Binary Programs: A Comparison with Factor-Width Partial Facial Reduction
Facial reduction (FR) is a preprocessing technique used to restore Slater's condition in semidefinite programming (SDP), but each step generally requires solving an auxiliary SDP. Factor-width-\(k\) partial FR restricts the class of exposing matrices. Increasing \(k\) enlarges this class, but, for \(k\geq3\), the auxiliary problem remains an SDP involving positive semidefinite blocks of order \(k\). For SDP relaxations of binary programs, we replace this auxiliary SDP by an LP-based face-identification method. We construct a polyhedron in subset-indexed moment variables that has polynomial size for fixed \(k\). The resulting face contains every feasible binary lift and is contained in every face exposed by a factor-width-\(k\) exposing matrix from the same auxiliary system. Thus, linear programming identifies a face no larger than those obtained from the factor-width-\(k\) auxiliary SDP while preserving all feasible binary points. To iterate the construction, we represent each identified face by linear equations in the original matrix variable, thereby retaining the moment-matrix indexing and the factor-width comparison at every iteration.