In catheterization laboratories (cath labs), doctors are required to perform invasive cardiovascu-lar procedures under a variety of specific constraints .Patients undergoing a treatment in a cath lab, generally also require preparative and aftercare at one of the hospital's wards, which complicate the scheduling pro-cess significantly .Still, in practice, scheduling of procedures for cath labs is mainly done by hand, which partly can be explained by the fact that many models make simplistic assumptions that ignore the actual practical complexity of the problem, such as the inherent randomness. In this paper, we propose an Integer Linear Programming based technique that integrates optimization for both cath labs and wards, while incorporating randomness within the scheduling process .Since the natural objective function is non-linear, the key insight for applying this method is that the objective function can be linearized under specific assumptions . These models have been tested on a case study of the VU Medical Center, for which the results are shown to be effective, as useful blueprints for the daily schedules are generated according to the preference of the hospital