A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
The traveling tournament problem with predefined venues
Journal of Scheduling
Recovering indirect solution densities for counting-based branching heuristics
CPAIOR'11 Proceedings of the 8th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
Counting-based search: branching heuristics for constraint satisfaction problems
Journal of Artificial Intelligence Research
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Exploiting solution counting information from individual constraints has led to some of the most efficient search heuristics in constraint programming. However, evaluating the number of solutions for the alldifferent constraint still presents a challenge: even though previous approaches based on sampling were extremely effective on hard instances, they are not competitive on easy to medium difficulty instances due to their significant computational overhead. In this paper we explore a new approach based on upper bounds, trading counting accuracy for a significant speedup of the procedure. Experimental results show a marked improvement on easy instances and even some improvement on hard instances. We believe that the proposed method is a crucial step to broaden the applicability of solution counting-based search heuristics.