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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 246543, 16 pages
Research Article

Nurse Scheduling Using Genetic Algorithm

1Excellence Center in Logistics and Supply Chain Management, Chiang Mai University, Chiang Mai 50200, Thailand
2Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand

Received 20 May 2014; Revised 20 October 2014; Accepted 23 October 2014; Published 27 November 2014

Academic Editor: Purushothaman Damodaran

Copyright © 2014 Komgrit Leksakul and Sukrit Phetsawat. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This study applied engineering techniques to develop a nurse scheduling model that, while maintaining the highest level of service, simultaneously minimized hospital-staffing costs and equitably distributed overtime pay. In the mathematical model, the objective function was the sum of the overtime payment to all nurses and the standard deviation of the total overtime payment that each nurse received. Input data distributions were analyzed in order to formulate a simulation model to determine the optimal demand for nurses that met the hospital’s service standards. To obtain the optimal nurse schedule with the number of nurses acquired from the simulation model, we proposed a genetic algorithm (GA) with two-point crossover and random mutation. After running the algorithm, we compared the expenses and number of nurses between the existing and our proposed nurse schedules. For January 2013, the nurse schedule obtained by GA could save 12% in staffing expenses per month and 13% in number of nurses when compare with the existing schedule, while more equitably distributing overtime pay between all nurses.