Optimising Personnel Rostering Through Mixed Integer Linear Programming
Master thesis
Permanent lenke
https://hdl.handle.net/11250/3104974Utgivelsesdato
2023Metadata
Vis full innførselSamlinger
- Master of Science [1711]
Sammendrag
Personnel planning is an important component of business management. Improved
personnel planning can lead to more satisfied employees and decreased personnel
costs. This thesis explores how mixed integer linear programming (MILP) can assist
the police´s operations centre with personnel planning, by allocating employees to
predefined shifts following legally required work regulations. Further, the effects of
recommended health-promoting shift patterns and employee satisfaction are explored.
The research finds that the optimisation model considering only the legally required
regulations, can provide complete schedules within a satisfactory time limit. However, when implementing recommended health-promoting shift patterns and personnel
preferences, the complexity of the model increases significantly. Key findings reflect
that the running time and complexity of the rostering problem increases significantly
when considering all regulations, preferences, and health-promoting shift patterns.
Hence, for the purpose of generating high quality solutions that considers all kinds of
preferences and regulations, also the less important ones, heuristics approaches should
be considered to obtain improved solutions more efficiently.
Beskrivelse
Masteroppgave(MSc) in Master of Science in Business Analytics, Handelshøyskolen BI, 2023