Partial constraint satisfaction
Artificial Intelligence - Special volume on constraint-based reasoning
Maintaining reversible DAC for Max-CSP
Artificial Intelligence
Radio Link Frequency Assignment
Constraints
Directed Arc Consistency Preprocessing
Constraint Processing, Selected Papers
Optimal Solutions for Frequency Assignment Problems via Tree Decomposition
WG '99 Proceedings of the 25th International Workshop on Graph-Theoretic Concepts in Computer Science
Constraint solving over semirings
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Russian doll search for solving constraint optimization problems
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Opportunistic Specialization in Russian Doll Search
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Solving weighted CSP by maintaining arc consistency
Artificial Intelligence
An efficient estimation function for the crew scheduling problem
Proceedings of the 2007 conference on Artificial Intelligence Research and Development
Multi-objective Russian Doll search
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
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Russian Doll Search (RDS) is a clever procedure to solve overconstrained problems. RDS solves a sequence of nested subproblems, where two consecutive subproblems differ in one variable only. We present the Specialized RDS (SRDS) algorithm, which solves the current subproblem for each value of the new variable with respect to the previous subproblem. The SRDS lower bound is superior to the RDS lower bound, which allows for a higher level of value pruning, although more work per node is required. Experimental results on random and real problems show that this extra work is often beneficial, providing substantial savings in the global computational effort.