By increasing number of patients, providing timely hygienic services is faced with some issues. Hence, improving healthcare conditions has received many attractions in the recent years. Master Surgery Scheduling and Surgical Case Assignment are considered as medium-term and short-term decision level problems, respectively. In this thesis, integration of both is investigated. In such integration, an operating room is assigned to all surgeons in a weekly manner, while the patients in waiting list are assigned to surgeons’ allocated time block, simultaneously. In order to enhance the efficiency and flexibility in scheduling, a set of time slots proportional to the time of each surgeon's surgeries is continuously assigned to each surgeon instead of allocating time blocks with predetermined time period. More over, we take into account the desirable days of surgeons for operation and the limited capacity of resources, i.e., beds in wards and intensive care units in scheduling. To the best of our knowledge, this problem hasn’t been addressed in the related works. To solve such problem, an objective function is defined which considers the patients in waitnig lists according to their priority. Then, a mixed-integer programming model is formulated. Since gaining optimal solution in higher dimensions is extremely time-consuming by mathematical model, it is decomposed into master surgery scheduling and surgical case assignment models. In order to solve surgical case assignment model, two heuristic methods based on rolling horizon approach and simulated annealing algorithm are developed. The mathematcal model and the proposed algorithms are evaluated by the real data achieved from Imam Hussein Specialized children's hospital. By comparing the results of sample problems, it became clear fix and optimize algorithm has the best solution quality. Finally, the performance of algorithms are compared with the actual conditions and the model efficiency is shown
