Operating rooms have become the most important areas in hospitals because of the scarcity and cost of resources. The present study investigates Operating room scheduling and rescheduling considering the priority of surgical patients in a specialized hospital. The ultimate purpose of scheduling is to minimize patient waiting time, surgeon idle time between surgeries, and penalties for deviations from Operating room preferences. A mathematical programming model is presented to solve the problem. Because the problem is strongly NP-hard, two heuristic algorithms are presented. A heuristic algorithm based on a mathematical programming model with local search obtains near-optimal solutions for all the samples. The average relative deviation of this algorithm is 0.02%. In continuous, heuristic algorithms performance have been investigated by increasing the number of patients and reduce the number of recovery beds. Next, a rescheduling heuristic algorithm is presented to deal with real-time situations. This algorithm presents fewer changes resulting from rescheduling in comparison with the scheduling problem.

Background and Objectives: Operating room (OR) scheduling is key to optimal Operating room productivity. The significant uncertainty associated with surgery duration renders scheduling of surgical operation a challenging task. This paper proposes a novel computational stochastic model to optimize scheduling of surgeries with uncertain durations. The model considers various surgical operation constraints in teaching hospitals, including optimal of assigning surgeons, residents, and assistant surgeons to each surgery, infection prevention constraints, availability of surgeons, and balanced distribution of operations between various groups of surgeons.Methods: A two-stage stochastic Operating room scheduling (SORS) framework was developed to minimize idle time and over time of ORs under practical constraints. The optimization model was solved using L-shaped algorithm. The performance of the SORS in proposing optimal scheduling solutions was extensively compared with that of deterministic models, as well as the performance of manual scheduling obtained from clinical data.Findings: Results from implication of model on sample real-life OR scheduling problems showed that SORS offers more efficient scheduling solutions as compared with the corresponding deterministic model. Furthermore, comparison of the SORS-proposed schedules with the practical schedules indicated that SORS can remarkably reduce the Operating room idle times (96%) and overtimes (87%), suggesting the utility of this model in clinical practice.Conclusions: A novel validated computational Operating room scheduling model was developed, which can potentially be employed to achieve higher Operating room performance.

Operating rooms (ORs) are among the most influential departments of a hospital that a major portion of its expenditures and revenues originate from it. Due to the limited resources and the presence of different stockholders, effective management, and the optimal planning of this department are challenging. This paper develops a mathematical model to address the integrated problem of the Operating room and surgical member scheduling with the objective of makespan minimization. In the proposed model, several aspects, including the availability and necessity of surgical members and equipment, and lunch break consideration, are incorporated. Finally, a case study related to an OR department in a general hospital is provided to assess the applicability and performance of the proposed model.

Given the increasing human need for health systems and the costs of using such systems, the problem of optimizing health-related systems has attracted the attention of many researchers. One of the most critical cases in this area is the Operating room scheduling. Much of the cost of health systems is related to Operating room costs. Therefore, planning and scheduling of Operating rooms can play an essential role in increasing the efficiency of health systems as well as reducing costs. Given the uncertain factors involved in such matters, attention to uncertainty in this problem is one of the most critical factors in the results. In this study, the problem of the daily scheduling of the Operating room with uncertain surgical time was investigated. For minimizing overhead costs and maximizing the number of surgeries to reduce patients' waiting time, after introducing a mathematical model, a chance-constrained programming approach is used to deal with its uncertainty. In this study, also, a harmony search algorithm is proposed to solve the model because of its NP-Hardness. By performing the numerical analysis and comparing the presented algorithm result with a genetic algorithm, the results show that the proposed algorithm has a better performance.