The Chv\'atal-Gomory Procedure for Integer SDPs with Applications in Combinatorial Optimization

TL;DR

This paper investigates the Chvátal-Gomory procedure for integer semidefinite programs, providing theoretical insights, new formulations, and an effective branch-and-cut algorithm that significantly improves solving large quadratic TSP instances.

Contribution

It introduces novel formulations and separation routines for CG cuts in ISDPs, and demonstrates their practical effectiveness in solving large QTSP instances.

Findings

The CG hierarchy for ISDPs converges with specific properties.

The branch-and-cut algorithm outperforms existing solvers on QTSP.

Numerical results show strong practical performance of the proposed method.

Abstract

In this paper we study the well-known Chv\'atal-Gomory (CG) procedure for the class of integer semidefinite programs (ISDPs). We prove several results regarding the hierarchy of relaxations obtained by iterating this procedure. We also study different formulations of the elementary closure of spectrahedra. A polyhedral description of the elementary closure for a specific type of spectrahedra is derived by exploiting total dual integrality for SDPs. Moreover, we show how to exploit (strengthened) CG cuts in a branch-and-cut framework for ISDPs. Different from existing algorithms in the literature, the separation routine in our approach exploits both the semidefinite and the integrality constraints. We provide separation routines for several common classes of binary SDPs resulting from combinatorial optimization problems. In the second part of the paper we present a comprehensive application of our approach to the quadratic traveling salesman problem (QTSP). Based on the algebraic connectivity of the directed Hamiltonian cycle, two ISDPs that model the QTSP are introduced. We show that the CG cuts resulting from these formulations contain several well-known families of cutting planes. Numerical results illustrate the practical strength of the CG cuts in our branch-and-cut algorithm, which outperforms alternative ISDP solvers and is able to solve large QTSP instances to optimality.