A generic arc-consistency algorithm and its specializations
Artificial Intelligence
Maintaining reversible DAC for Max-CSP
Artificial Intelligence
Range-Based Algorithm for Max-CSP
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Node and arc consistency in weighted CSP
Eighteenth national conference on Artificial intelligence
Meta-constraints on violations for over constrained problems
ICTAI '00 Proceedings of the 12th IEEE International Conference on Tools with Artificial Intelligence
Arc consistency for soft constraints
Artificial Intelligence
Solving weighted CSP by maintaining arc consistency
Artificial Intelligence
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Temporal constraint reasoning with preferences
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Virtual Arc consistency for weighted CSP
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Towards efficient consistency enforcement for global constraints in weighted constraint satisfaction
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Expert Systems with Applications: An International Journal
Flexible management of large-scale integer domains in CSPs
SETN'10 Proceedings of the 6th Hellenic conference on Artificial Intelligence: theories, models and applications
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The weighted constraint satisfaction problem (WCSP) is a soft constraint framework with a wide range of applications. Most current complete solvers can be described as a depth-first branch and bound search that maintains some form of local consistency during the search. However, the known consistencies are unable to solve problems with huge domains because of their time and space complexities. In this paper, we adapt the 2B-consistency, a weaker form of arc consistency well-known in classic CSPs, into the bound arc consistency and we provide several algorithms to enforce it.