A flexible iterative improvement heuristic to support creation of feasible shift rosters in self-rostering

Self-rostering is receiving more and more attention in literature and in practice. With self-rostering, employees propose the schedule they prefer to work during a given planning horizon. However, these schedules often do not match with the stang demand as specfied by the organization. We resent an approach to support creating feasible schedules that uses the schedules proposed by the employees as input and that aims to divide the burden of shift reassignments fairly throughout the employees. We discuss computational results and indicate how various model parameters influence scheduling performance indicators. The presented approach is flexible and easily extendable, since labor rule checks are isolated from the actual algorithm, which makes it easy to include additional labor rules in the approach. Moreover, our approach enables the user to make a trade-off between the quality of the resulting roster and the extent to which the planner is able to track the decisions of the algorithm.