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Solving the Nurse Scheduling Problem of Private Hospitals in the Philippines using Various Operators for Genetic Algorithm
Objectives: This paper aims to find the most efficient crossover and mutation operators for genetic algorithms in solving the Nurse Scheduling Problem (NSP) for private hospitals in the Philippines. Methods/Statistical Analysis: In this study, different combinations of three crossover and three mutation operators commonly used for Genetic Algorithms (GA) are tested and compared in order to evaluate their efficiency in providing a solution for the NSP. The GA, using the nine different combinations of operators, is then applied to obtain schedules of a particular private hospital in the Philippines. Findings: Results of the study show that the pair two-point crossover and single mutation operators provide a better timetable for nurses at a private hospital in the Philippines in terms of accommodating nurses’ preferences and reducing salary costs.Application/Improvements: Private hospitals aiming to find a schedule that respects both the preferences of the nurses and fulfills the objectives of the hospital will find results of this study useful.
Genetic Algorithm, Nurse Scheduling, Private Hospitals, Philippines.
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