Efficient structural symmetry breaking for constraint satisfaction problems

Symmetry breaking for constraint satisfaction problems (CSPs) has attracted considerable attention in recent years. Various general schemes have been proposed to eliminate symmetries. In general, these schemes may take exponential space or time to eliminate all the symmetries. We identify several classes of CSPs that encompass many practical problems and for which symmetry breaking for various forms of value and variable interchangeability is tractable using dedicated search procedures or symmetry-breaking constraints that allow nogoods and their symmetrically equivalent solutions to be stored and checked efficiently

Reduction Techniques in Constraint Programming and Combinatorial Optimization

von Meinolf SellmannPaderborn, Univ., Diss., 200

Approximated Consistency for the Automatic Recording Constraint

We introduce the automatic recording constraint (ARC) that can be used to model and solve scheduling problems where tasks may not overlap in time and the tasks linearly exhaust some resource. Since achieving generalized arc-consistency for the ARC is NP-hard, we develop a filtering algorithm that achieves approximated consistency only. Numerical results show the benefits of the new constraint on three out of four different types of benchmark sets for the automatic recording problem. On these instances, run-times can be achieved that are orders of magnitude better than those of the best previous constraint programming approach

Disco-novo-gogo: Integrating local search and complete saerch with restarts

A hybrid algorithm is devised to boost the performance of complete search on under-constrained problems. We suggest to use random variable selection in combination with restarts, augmented by a coarse-grained local search algorithm that learns favorable value heuristics over the course of several restarts. Numerical results show that this method can speedup complete search by orders of magnitude