New methods to color the vertices of a graph
Communications of the ACM
The Brélaz Heuristic and Optimal Static Orderings
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
Finding diverse and similar solutions in constraint programming
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Coordination by design and the price of autonomy
Autonomous Agents and Multi-Agent Systems
Generalizing constraint satisfaction on trees: Hybrid tractability and variable elimination
Artificial Intelligence
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Evaluating and Improving Modern Variable and Revision Ordering Strategies in CSPs
Fundamenta Informaticae - RCRA 2008 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
Learning cluster-based structure to solve constraint satisfaction problems
Annals of Mathematics and Artificial Intelligence
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One of the key factors in the efficiency of backtracking algorithms is the rule they use to decide on which variable to branch next (namely, the variable ordering heuristics). In this paper, we give a formulation of dynamic variable ordering heuristics that takes into account the properties of the neighborhood of the variable.