New nurse scheduling model considering nurses’ seniority and the possibility of consecutive shifts under COVID-19 (A real case study)

ABSTRACT

The nurse scheduling problem is the assignment of nurses to different working shifts while considering the existing constraints and rules. In recent years, medical centers have faced the challenge of resource planning due to the COVID-19 pandemic. In this study, a new mathematical model is formulated for nurse scheduling under the pandemic. In this model the nurses are categorized based on seniority and the auxiliary nurses are used because of the staff shortage. Apart from the hospital rules, conditions imposed during the COVID-19 pandemic are also considered. The proposed model is formulated in such a way that undesirable shifts are minimized, and also the violation of the schedule in the case of the possible absence of a nurse is prevented due to the model's robustness. The formulated model is applied in a real case in Iran, and the Genetic Algorithm (GA) is used as the solution method. To justify the Genetic Algorithm, different examples are generated and solved using this algorithm and the exact method. The results indicate that the Genetic Algorithm can provide near-optimal solutions with a mean optimality gap of 0.65% in a reasonable CPU time. The resulting timetable minimizes undesirable shifts and the utilization of auxiliary nurses.

KEYWORDS:

• Nurse scheduling
• mathematical model
• COVID-19
• Genetic Algorithm
• auxiliary nurses

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Notes on contributors

Saman Malekian

Saman Malekian received his MSc in Industrial Engineering from Islamic Azad University of South Tehran Branch in 2016. He is a PhD student in Industrial Engineering at Islamic Azad University. He has been involved in several studies related to maintenance management, scheduling problems, decision making approaches, and data envelopment analysis. He is currently continuing his research with Dr. Rashidi Komijan.

Alireza Rashidi Komijan

Alireza Rashidi Komijan is an Associate Professor of Industrial Engineering. He received his PhD from Islamic Azad University in 2009. His major is operations research with focus on mathematical modelling, especially air transportation models. His research interest is large-scale scheduling problems.

Ahmad Shoja

Ahmad Shoja is an Assistant Professor of Applied Mathematics. He received his PhD from Islamic Azad University in 2014. His major is mathematical and industrial engineering with focus on mathematical modelling. He has been involved in several studies related to mathematical sciences and nonlincar modelling.

Mohammad Ehsanifar

Mohammad Ehsanifar is an Associate Professor of Industrial Engineering. He received his PhD from Islamic Azad University in 2012. He also completed his Postdoctoral research in 2017. His major is operations research with focus on mathematical modeling. His research interest is nonparametric statistics and systems thinking.