Computers and Operations Research
Variable Neighborhood Decomposition Search
Journal of Heuristics
Specific Filtering Algorithms for Over-Constrained Problems
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
A hybrid AI approach for nurse rostering problem
Proceedings of the 2003 ACM symposium on Applied computing
Arc consistency for soft constraints
Artificial Intelligence
The State of the Art of Nurse Rostering
Journal of Scheduling
A 0-1 goal programming model for nurse scheduling
Computers and Operations Research
On global warming: Flow-based soft global constraints
Journal of Heuristics
Models for Global Constraint Applications
Constraints
Softening Gcc and Regular with preferences
Proceedings of the 2009 ACM symposium on Applied Computing
Virtual Arc consistency for weighted CSP
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A shift sequence based approach for nurse scheduling and a new benchmark dataset
Journal of Heuristics
Generalized arc consistency for global cardinality constraint
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Hybrid optimization techniques for the workshift and rest assignment of nursing personnel
Artificial Intelligence in Medicine
Applying constraint programming to identification and assignment of service professionals
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
Identifying patterns in sequences of variables
CPAIOR'11 Proceedings of the 8th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
On matrices, automata, and double counting
CPAIOR'10 Proceedings of the 7th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
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Nurse Rostering Problems (NRPs) consist of generating rosters where required shifts are assigned to nurses over a scheduling period satisfying a number of constraints. Most NRPs in real world are NP-hard and are particularly challenging as a large set of different constraints and specific nurse preferences need to be satisfied. The aim of this paper is to show how NRPs can be easily modelled and efficiently solved using soft global constraints. Experiments on real-life problems and comparison with ad'hoc OR approaches are detailed.