چكيده لاتين
face the challenge of effectively planning and scheduling operating rooms as cost and revenue centers for hospitals. The planning and scheduling of available resources in hospital surgical departments, including rooms, surgeons, nurses, and post-operative downstream resources, play a significant role in improving hospital productivity. This thesis presents a two-stage method for the integrated scheduling of operating room human resources. In the first stage, the master surgery scheduling (MSS) problem is modeled in two scenarios: the absence/presence of an uncertain component for demand. In the first scenario, a main surgical schedule is provided by determining the combination of patients in time blocks along with the number of required daily shift nurses. In the second scenario, in addition to these factors, the number of on-call nurses needed to cover the uncertain demand component is also calculated. Then, in the second stage, using the outputs from the first stage, operating room nurses are scheduled, and a monthly shift plan for them is created. The advantages of this matter include planning surgical operations while considering the limitations of nurses, and on the other hand, scheduling nurses according to the workload for each day and shift. Additionally, an integrated examination of these two issues will ensure the necessary nursing specialties are available each day within the planning period, taking into account the scheduled operations for that day, and will create greater coordination in the surgical department. The goals of the first phase are to minimize unmet demand, minimize overtime and idle time in operating rooms, minimize the maximum number of nurses needed daily, and minimize the bed-sharing rate between inpatient departments. In the second phase, the goals focus on minimizing the maximum number of nurses required daily, leveling the workload of nurses, and maximizing nurse satisfaction and preferences. The limitations of downstream resources, including the intensive care unit and inpatient wards, have been considered, and the inpatient wards have the potential to share beds based on the type of equipment and services they provide. To calculate bed occupancy, two types of patients have been considered: those who enter the downstream units after surgery and those who seek to use the inpatient wards without undergoing surgery. To identify the problem environment, constraints, and available resources, interviews with experts from Amol Hospital and Imam Hossein Childrenʹs Hospital have been utilized, and random data has been used to solve the proposed models. Finally, a set of efficient solutions for the four-objective and three-objective optimization problems has been presented. The other influencing factors and parameters of the proposed models were also examined and analyzed, revealing that the most influential parameter in the proposed models is the coefficients of the normalized objective functions. By reviewing the results of the solution for different values of the objective function coefficients, it was determined that the two objective functions of unmet demand and overtime and room unemployment are of greater importance. Additionally, the results indicate that the importance coefficient of unemployment has a greater impact on the values of the objective function and the productivity of the sectors compared to overtime. In the nurse scheduling model, determining the penalty values related to not meeting the nursesʹ preferences does not significantly affect the objective functions and the satisfaction of the nurses, but it does influence the fulfillment of the nursesʹ requests.
