Comparative Performance of Simulated Annealing and Genetic Algorithm in Solving Nurse Scheduling Problem.

Nurse Scheduling Problems (NSP) represent a subclass of scheduling problems that are hard to solve. The goal is to find high quality shift and resource assignments, in accordance with the labor contract rules, satisfying the requirements of employees as well as the employers in health-care institutions. The Nurse Scheduling Problems (NSP) can be viewed as Constraint Satisfaction Problem (CSP) where the constraints are classified as hard and soft constraints. In this paper, a real case of a cyclic nurse Scheduling problem is introduced. This means that the generated roster 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. [ABSTRACT FROM AUTHOR]