NURSE ROSTERING PROBLEMS USING GENETIC ALGORITHM AND SIMULATED ANNEALING
Abstract
Nurse Roistering Problems (NRP) represent a subclass of selecting problems that are hard to solve. The goal is to find high quality shift and resource assignments, inaccordance with the labor requirements of employees as well as the employers in healthcare institutions. The Nurse Rostering Problems (NRP) can be viewed as Constraint Satisfaction Problem (CSP) where the constraints are classified as hard and soft constraints. In this work, a real case of a cyclic nurse Rostering problem is introduced. This means that the generated roaster can be repeated indefinitely if no further constraint is introduced. We use two different methods, namely, Simulated Annealing and Genetic Algorithm to solve this problem and compared their performances at different difficulty Levels.
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