  We describe a hybrid procedure for solving the traveling salesman problem
(TSP) to provable optimality. We first sparsify the instance, and then use a
hybrid algorithm that combines a branch-and-cut TSP solver with a Hamiltonian
cycle problem solver. We demonstrate that this procedure enables us to solve
difficult instances to optimality, including one which had remained unsolved
since its construction in 2002.
