Nurse rostering with fatigue modelling: incorporating a validated sleep model with biological variations in nurse rostering

Kjartan Kastet Klyve, Ilankaikone Senthooran, Mark Wallace

Research output: Contribution to journalArticleResearchpeer-review


We use a real Nurse Rostering Problem and a validated model of human sleep to formulate the Nurse Rostering Problem with Fatigue. The fatigue modelling includes individual biologies, thus enabling personalised schedules for every nurse. We create an approximation of the sleep model in the form of a look-up table, enabling its incorporation into nurse rostering. The problem is solved using an algorithm that combines Mixed-Integer Programming and Constraint Programming with a Large Neighbourhood Search. A post-processing algorithm deals with errors, to produce feasible rosters minimising global fatigue. The results demonstrate the realism of protecting nurses from highly fatiguing schedules and ensuring the alertness of staff. We further demonstrate how minimally increased staffing levels enable lower fatigue, and find evidence to suggest biological complementarity among staff can be used to reduce fatigue. We also demonstrate how tailoring shifts to nurses’ biology reduces the overall fatigue of the team, which means managers must grapple with the issue of fairness in rostering.

Original languageEnglish
Pages (from-to)21–45
Number of pages25
JournalHealth Care Management Science
Publication statusPublished - Mar 2023


  • Constraint programming
  • Fatigue
  • Large neighbourhood search
  • Mixed-Integer programming
  • Nurse rostering
  • Operations research
  • Sleep

Cite this