The Staff Scheduling Problem involves finding an optimal way to assign people to meet work requirements, allowing for a variety of constraints. The modelled situations are often complex and difficult to solve. A special case, often used to represent the whole category, is called the Nurse Scheduling Problem or the Nurse Rostering Problem. Potential solution techniques include: mixed integer programming, constraint satisfaction, and genetic algorithms.
Key features of this model:
- Description: Roster nurses to shifts.
- Category: Staff scheduling.
- Type: Constraint satisfaction.
- Library: OR-Tools.
- Solver: CpSolver.
- Source: www.hakank.org
Source has been converted to a Jupyter notebook:
- Import of cp_sat_utils has been commented out, as the custom library is not used in this model.
Key features of this model:
- Description: Schedule Post Office staff to meet demand.
- Category: Staff scheduling.
- Type: Constraint satisfaction.
- Library: OR-Tools.
- Solver: CpSolver.
- Source: www.hakank.org
Source has been modified:
- Converted to a Jupyter notebook.
- The original model appears to be wrong, so a constraint has been corrected.
- Added an additional component to the objective function.
- Extended the output to provide additional information about the solution.
