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Solving the Nurse Scheduling Problem of Private Hospitals in the Philippines using Various Operators for Genetic Algorithm

Affiliations

  • Department of Mathematical Sciences, College of Arts and Sciences, Mindanao University of Science and Technology, Lapasan, Cagayan de Oro City, 9000, Philippines
  • Agusan National High School, A.D. Curato St., Butuan City, 8600, Philippines

Abstract


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.

Keywords

Genetic Algorithm, Nurse Scheduling, Private Hospitals, Philippines.

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