Abstract
Recently, the emergency department (ED) has been experiencing overcrowding, which causes numerous problems for both patients and employees. This situation leads to an increased length of stay in the ED for arrivals, as well as financial losses for the hospital. Emergency services play a crucial role in society, as people require them at any time without a prior appointment. The ED is a not-simple due to the diversity of resources available and the unpredictable nature of emergencies. Recently, many researchers have focused on shortening the length of patient stays in the emergency department in order to reduce the pressure on medical staff and improve the quality of medical services provided. In this paper, we propose a new method based on a multi-objective algorithm, such as multi-objective particle swarm optimization (MOPSO), and colored Petri nets. The emergency department is modeled using colored Petri nets. After running the simulation model, initial results are obtained. In order to modify human resource counts within the simulation model, MOPSO algorithms are used. This approach helps hospital decision-makers identify optimal solutions for managing human resources in the emergency department.
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