Identifying underlying structures in combinatorial optimisation problems leads to a better understanding of a problem and, consequently, to efficient solution methodologies. The present paper introduces a new network flow formulation for a large class of nurse rostering problems. By solving an integer minimum cost flow problem in a carefully constructed network, nurses’ shift schedules can be c...

Nurse rostering is a difficult search problem with many constraints. In the literature, a number of approaches have been investigated including penalty function methods to tackle these constraints within genetic algorithm frameworks. In this paper, we investigate an extension of a previously proposed stochastic ranking method, which has demonstrated superior performance to other constraint hand...

This contribution deals with the distributed version of the nurse rostering problem. It is considered in a hospital with many separated wards. The nurse rostering problem within a ward is ‘the local problem’, rosters within a ward are ‘local rosters’. At any time in the process, i.e. at the time of the construction of a roster for a certain time period as well as in the course of this time peri...

Nursing staff is principally cyclically scheduled in various hospitals in Belgium. The employed cyclic schedules embody, however, only a weak reflection of the ultimate nurse rosters constructed for a specific month. In this paper we investigate the benefits of integrating nurse-specific characteristics in the cyclic scheduling approach. Moreover, we analyze to what extent these characteristics...

In recent years genetic algorithms have emerged as a useful tool for the heuristic solution of complex discrete optimisation problems. In particular there has been considerable interest in their use in tackling problems arising in the areas of scheduling and timetabling. However, the classical genetic algorithm paradigm is not well equipped to handle constraints and successful implementations u...