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

Autor: Milad Asadpour, Samineh Shirmohammadi, Atefeh Amindoust
Jazyk: angličtina
Rok vydání: 2021
Předmět:
2019-20 coronavirus outbreak
Schedule
Medicine (General)
Operations research
Coronavirus disease 2019 (COVID-19)
Article Subject
Computer science
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
0211 other engineering and technologies
Biomedical Engineering
Personnel Staffing and Scheduling
Nurses
Health Informatics
02 engineering and technology
Nursing
Iran
R5-920
Nurse scheduling problem
Factor (programming language)
Genetic algorithm
0202 electrical engineering
electronic engineering
information engineering
Medical technology
Humans
R855-855.5
Fatigue
computer.programming_language
021103 operations research
COVID-19
Reproducibility of Results
Models
Theoretical
Hospitals
020201 artificial intelligence & image processing
Surgery
computer
Algorithms
Biotechnology
Research Article
Zdroj: Journal of Healthcare Engineering
Journal of Healthcare Engineering, Vol 2021 (2021)
ISSN: 2040-2295
DOI: 10.1155/2021/5563651
Popis: 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.
Databáze: OpenAIRE
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