Treewidth-based conditions for exactness of the Sherali-Adams and Lasserre relaxations

The Sherali-Adams (SA) and Lasserre (LS) approaches are “lift-and-project” methods that generate nested sequences of linear and/or semidefinite relaxations of an arbitrary 0-1 polytope P ⊆ [0, 1]n. Although both procedures are known to terminate with an exact description of P after n steps, there are various open questions associated with characterizing, for particular problem classes, whether exactness is obtained at some step s < n. This paper provides sufficient conditions for exactness of these relaxations based on the hypergraph-theoretic notion of treewidth. More specifically, we relate the combinatorial structure of a given polynomial system to an underlying hypergraph. We prove that the complexity of assessing the global validity of moment sequences, and hence the tightness of the SA and LS relaxations, is determined by the treewidth of this hypergraph. We provide some examples to illustrate this characterization.

[1]  Vasek Chvátal,et al.  Edmonds polytopes and a hierarchy of combinatorial problems , 1973, Discret. Math..

[2]  Claude Berge,et al.  Graphs and Hypergraphs , 2021, Clustering.

[3]  Hanif D. Sherali,et al.  A Hierarchy of Relaxations Between the Continuous and Convex Hull Representations for Zero-One Programming Problems , 1990, SIAM J. Discret. Math..

[4]  Alexander Schrijver,et al.  Cones of Matrices and Set-Functions and 0-1 Optimization , 1991, SIAM J. Optim..

[5]  Hans L. Bodlaender,et al.  A Tourist Guide through Treewidth , 1993, Acta Cybern..

[6]  Steffen L. Lauritzen,et al.  Graphical models in R , 1996 .

[7]  Tamon Stephen,et al.  On a Representation of the Matching Polytope Via Semidefinite Liftings , 1999, Math. Oper. Res..

[8]  Michael I. Jordan,et al.  Probabilistic Networks and Expert Systems , 1999 .

[9]  Jean B. Lasserre,et al.  Global Optimization with Polynomials and the Problem of Moments , 2000, SIAM J. Optim..

[10]  Jean B. Lasserre,et al.  An Explicit Equivalent Positive Semidefinite Program for Nonlinear 0-1 Programs , 2002, SIAM J. Optim..

[11]  Monique Laurent,et al.  A Comparison of the Sherali-Adams, Lovász-Schrijver, and Lasserre Relaxations for 0-1 Programming , 2003, Math. Oper. Res..

[12]  Pablo A. Parrilo,et al.  Semidefinite programming relaxations for semialgebraic problems , 2003, Math. Program..

[13]  Alexander Schrijver,et al.  Combinatorial optimization. Polyhedra and efficiency. , 2003 .

[14]  Martin J. Wainwright,et al.  LP Decoding Corrects a Constant Fraction of Errors , 2004, IEEE Transactions on Information Theory.

[15]  Monique Laurent,et al.  Semidefinite Relaxations for Max-Cut , 2004, The Sharpest Cut.

[16]  Martin J. Wainwright,et al.  Using linear programming to Decode Binary linear codes , 2005, IEEE Transactions on Information Theory.