A Hybrid Genetic Algorithm for Nurse Scheduling Problem considering the Fatigue Factor

被引:20
作者
Amindoust, Atefeh [1 ]
Asadpour, Milad [1 ,2 ]
Shirmohammadi, Samineh [3 ]
机构
[1] Islamic Azad Univ, Najafabad Branch, Dept Ind Engn, Najafabad, Iran
[2] Univ Auckland, Sch Business, Dept Informat Syst & Operat Management, Auckland, New Zealand
[3] Islamic Azad Univ, Najafabad Branch, Young Researchers & Elite Club, Najafabad, Iran
关键词
ROSTERING PROBLEM; OPTIMIZATION;
D O I
10.1155/2021/5563651
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Nowadays and due to the pandemic of COVID-19, nurses are working under the highest pressure benevolently all over the world. This urgent situation can cause more fatigue for nurses who are responsible for taking care of COVID-19 patients 24 hours a day. Therefore, nurse scheduling should be modified with respect to this new situation. The purpose of the present research is to propose a new mathematical model for Nurse Scheduling Problem (NSP) considering the fatigue factor. To solve the proposed model, a hybrid Genetic Algorithm (GA) has been developed to provide a nurse schedule for all three shifts of a day. To validate the proposed approach, a randomly generated problem has been solved. In addition, to show the applicability of the proposed approach in real situations, the model has been solved for a real case study, a department in one of the hospitals in Esfahan, Iran, where COVID-19 patients are hospitalized. Consequently, a nurse schedule for May has been provided applying the proposed model, and the results approve its superiority in comparison with the manual schedule that is currently used in the department. To the best of our knowledge, it is the first study in which the proposed model takes the fatigue of nurses into account and provides a schedule based on it.
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页数:11
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