Article ID: | iaor20171137 |
Volume: | 27 |
Issue: | 1 |
Start Page Number: | 83 |
End Page Number: | 101 |
Publication Date: | Mar 2017 |
Journal: | International Journal of Services and Operations Management |
Authors: | Nasiri Mohammad Mahdi, Rahvar Meysam |
Keywords: | scheduling, combinatorial optimization, programming: multiple criteria, simulation, timetabling, programming: mathematical, heuristics |
The nurse scheduling problem (NSP) has received special attention during the recent decades. The difficulty of generating tables manually alongside the shortage of nurses and prohibition of outsourcing nurses has led to hectic schedules in which assigning three consecutive shifts (i.e., 24 hour shift) to a nurse could be seen. Furthermore, nurses' preferences are usually neglected because the concentration is on meeting the nursing requirements. In this paper, we propose a multi‐objective mathematical model in which we tackle the main inefficiency of the system (i.e., three consecutive shifts). We also try to maximise nurses' preferences. In addition to the presentation of a new mathematical model, we use the novel method of augmented epsilon constraint to generate several tables. To deal with the complexity of NSP, we use a two‐step approach. We find the efficient solutions over the Pareto set, among which we select the best table.