Tractable Benchmarks For Constraint Programming
Justyna Petke and Peter Jeavons
The general constraint satisfaction problem for variables with finite domains is known to be NP-complete, but many different conditions have been identified which are sufficient to ensure that classes of instances satisfying those conditions are tractable, that is, solvable in polynomial time. Results about tractability have generally been presented in theoretical terms, with little discussion of how these results impact on practical constraint-solving techniques. In this paper we investigate the performance of several standard constraint solvers on benchmark instances that are designed to satisfy various different conditions that ensure tractability. We show that in certain cases some existing solvers are able to automatically take advantage of the problem features which ensure tractability, and hence solve the corresponding instances very efficiently. However, we also show that in many cases the existing pre-processing techniques and solvers are unable to solve efficiently the families of instances of tractable problems that we generate. We therefore suggest that such families of instances may provide useful benchmarks for improving pre-processing and solving techniques.