Meinolf Sellmann, Carlos Ansotegui
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 speed-up complete search by orders of magnitude.
Subjects: 15. Problem Solving; 15.2 Constraint Satisfaction
Submitted: May 13, 2006