We consider a Hamiltonian decomposition problem of partitioning a regular graph into edge-disjoint Hamiltonian cycles. It is known that verifying vertex nonadjacency in the 1-skeleton of the symmetric and asymmetric traveling salesperson polytopes is an NP-complete problem. On the other hand, a sufficient condition for two vertices to be nonadjacent can be formulated as a combinatorial problem of finding a Hamiltonian decomposition of a 4-regular multigraph. We present two backtracking algorithms for verifying vertex nonadjacency in the 1-skeleton of the traveling salesperson polytope and constructing a Hamiltonian decomposition: an algorithm based on a simple path extension and an algorithm based on the chain edge fixing procedure. According to the results of computational experiments for undirected multigraphs, both backtracking algorithms lost to the known heuristic general variable neighborhood search algorithm. However, for directed multigraphs, the algorithm based on chain edge fixing showed comparable results with heuristics on instances with the existing solution and better results on instances of the problem where the Hamiltonian decomposition does not exist.
We consider a Hamiltonian decomposition problem of partitioning a regular multigraph into edge-disjoint Hamiltonian cycles. It is known that verifying vertex nonadjacency in the 1-skeleton of the symmetric and asymmetric traveling salesperson polytopes is an NP-complete problem. On the other hand, a sufficient condition for two vertices to be nonadjacent can be formulated as a combinatorial problem of finding a Hamiltonian decomposition of a 4-regular multigraph. We present two backtracking algorithms for verifying vertex nonadjacency in the 1-skeleton of the traveling salesperson polytope and constructing a Hamiltonian decomposition: an algorithm based on a simple path extension and an algorithm based on the chain edge fixing procedure. According to the results of computational experiments for undirected multigraphs, both backtracking algorithms lost to the known general variable neighborhood search algorithm. However, for directed multigraphs, the algorithm based on chain edge fixing showed comparable results with heuristics on instances with the existing solution and better results on instances of the problem where the Hamiltonian decomposition does not exist.
R
graph
multigraph
D
heuristic