Hospitals are the major clinical centers in most countries. In this thesis, due to the limited resources and available beds in each hospital, the patient admission scheduling problem has been studied. This problem concerns assigning patients to rooms, taking into consideration patient preferences as well as satisfying necessary treatment specialism. The aim is to determine the patient's bed to maximize the efficiency of using different resources. According to the complexity of the problem, most of the papers have proposed heuristic and meta-heuristic methods to solve the problem. To increase patient's satisfaction, we propose a new mixed-integer programming model incorporating all constraints from the literature reduced the problem solution time by providing efficient cuts, modeling constraints, and using the warm start approach. The benchmark instances in the literature were solved to illustrate the efficiency of the proposed model.