Solving the multi-objective nurse scheduling problem with a weighted cost function

Solving the multi-objective nurse scheduling problem with a weighted cost function

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Article ID: iaor20083209
Country: Germany
Volume: 155
Issue: 1
Start Page Number: 279
End Page Number: 288
Publication Date: Nov 2007
Journal: Annals of Operations Research
Authors: ,
Keywords: personnel & manpower planning, heuristics, optimization: simulated annealing
Abstract:

The primary objective of the nurse scheduling problem is to ensure there are sufficient nurses on each shift. There are also a number of secondary objectives designed to make the schedule more pleasant. Neighbourhood search implementations use a weighted cost function with the weights dependent on the importance of each objective. Setting the weights on binding constraints so they are satisfied but still allow the search to find good solutions is difficult. This paper compares two methods for overcoming this problem, SAWing and Noising with simulated annealing and demonstrates that Noising produces better schedules.

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