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

Abstract

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.