The State of the Art of Nurse Rostering
Journal of Scheduling
Nurse rostering using constraint programming and meta-level reasoning
IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
A hybrid setup for a hybrid scenario: combining heuristics for the home health care problem
Computers and Operations Research
Expert Systems with Applications: An International Journal
An evolutionary squeaky wheel optimization approach to personnel scheduling
IEEE Transactions on Evolutionary Computation
Constraint-based rostering using meta-level reasoning and probability-based ordering
Engineering Applications of Artificial Intelligence
Journal of Artificial Intelligence Research
Iterated local search in nurse rostering problem
Proceedings of the Fourth Symposium on Information and Communication Technology
OPTIMIZING COST IN SOFTWARE DEVELOPMENT PROJECTS
Journal of Integrated Design & Process Science
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The paper describes the design and implementation of a constraint-based nurse rostering system using a redundant modeling approach. Nurse rostering is defined as the process of generating timetables for specifying the work shifts of nurses over a given period of time. This process is difficult because the human roster planner has to ensure that every rostering decision made complies with a mixture of hard hospital rules and soft nurse preference rules. Moreover, some nurse shift pre-assignments often break the regularity of wanted (or unwanted) shifts and reduce the choices for other unfilled slots. Soft constraints amount to disjunction, which can be modeled as choices in the search space. This approach, although straightforward, incurs overhead in the search of solution. To reduce search time, the authors propose redundant modeling, an effective way to increase constraint propagation through cooperation among different models for the same problem. The problem domain involves around 25 to 28 nurses and 11 shift types. Experiments and pilot testing of the system confirm the effectiveness and efficiency of the method.