Operating scheduling is a crucial part of a hospital management. It is related to both patient satisfaction and hospital performance. This thesis considers elective surgery scheduling problems at the tactical level to determine the number of time slots for different elective surgeries. There are multiple objectives, including minimizing the number of overdue patients, number of patients on the waiting list, number of days patients waiting after expected days and maximizing the hospital revenue and performance. All these objectives are fulfilled under the resource limitation, such as the number of wards, the number of beds, the number of ICU rooms, the number of surgeons, and the number of operating theatres are considered in the model as well. Variable neighbourhood search (VNS) algorithm is used in this research to solve the operating scheduling problem. The VNS algorithm in this thesis is composed of several local search schemes based on different neighbourhood structures. A numerical experiment is performed in the randomly generated data set to evaluate the effectiveness of the proposed algorithm. To improve the generalization so that the algorithm can be used in hospitals of different sizes and for different planning periods, we consider several combinations of the number of surgical departments, surgery types and time horizon. In this way, the result of this research is more practical and robust to solve operating theatre scheduling problems of different sizes of hospitals. By using the VNS algorithm in elective surgery operating room scheduling, we hope to increase patients’ satisfaction and reduce the cost of hospitals at the same time.