This paper discusses and analyses the tradeoff between the flexibility afforded with greater number of staff and the implied cost of employing extra staff in the context of the nurse-scheduling problem. If the number of staff is constant, our study allows quantification of the degree of pressure put on the staff resulting from the schedules that do not satisfy their preferences for shift allocation. We present a practical approach, based on our domain transformation methodology that achieves good quality schedules without high computational requirements.

Nurse Rostering problems represent a subclass of scheduling problems that are hard to solve. Their complexity is due to the large solution spaces and the many objectives and constraints that need to be fulfilled. In this study, we propose a hierarchical method of granulation of problem domain through preprocessing of constraints. A set of zero-cost patterns in the granulated search space provides a basis for the generation of work schedules. Feasible schedules calculated for week 1 are used to define zero-cost shift patterns that can be deployed in week 2. These in turn are used for the generation of feasible schedules for week 2. The process can be applied over the extended time frame. We show that the granulation of the problem description in terms of constraints and scheduling time frames leads to a more manageable computing task.

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The nurse scheduling problem (NSP) is a complex optimisation problem regarding the allocation of nurses to duty rosters in hospitals.