Constraint Optimization For Nurse Rostering Using Particle Swarm Optimization With Global Optimum Test Function

Norazira, A Jalil (2012) Constraint Optimization For Nurse Rostering Using Particle Swarm Optimization With Global Optimum Test Function. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

The decision making in assigning all nursing staffs to shift duties in a hospital unit must be done appropriately because it is a difficult task due to various requirements and constraints that need to be fulfilled. The shift assignment or also known as roster has a great impact on the nurses' operational circumstances which are strongly related to the intensity of quality of health care. The head nurse usually spends a substantial amount of time developing manual rosters, especially when there are many staff requests. Yet, sometimes she could not ensure that all constraints are met. Therefore, this research identified the relevant constraints being imposed in optimizing the nurse rostering problem and examined the efficient method to generate the nurse roster based on constraints involved. Subsequently, as part of this research, we use a Particle Swarm Optimization (PSO) to solve this problem. The proposed PSO technique is evaluated for its efficiency, where 50 samples of rosters generated were taken for analysis. The feasible solutions were evaluated based on their minimum penalty values. The penalty values were given based on different violations of soft constraints. The PSO technique is able to optimize the soft constraints as much as possible.

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