###### Abstract
For example, [PERSON] and [PERSON] [11] developed a master surgery schedule and proposed a stochastic programming model to integrate the medium-level decision-making of operating rooms with downstream departments such as intensive care units and wards. [PERSON] and [PERSON] [12] studied the master surgery scheduling problem on a medium level along with the surgical case assignment problem. They proposed a mixed integer nonlinear programming model and hybrid metaheuristics to solve the problem. Additionally, [PERSON] et al. [13] studied the medium-level planning problem to calculate the demand distribution of downstream departments for a given master surgery schedule in a hospital. Lower-level planning has also been investigated in the literature. For example, [PERSON] and [PERSON] [14] studied operation room planning and the scheduling problem as a generalized job shop scheduling problem. They developed a mixed integer linear programming model to minimize the makespan of surgeries at a lower-level planning horizon. [PERSON] et al. [15] studied the problem of elective patient scheduling at a lower-level planning horizon to maximize operating room utilization based on patient prioritization. They developed an integer programming model and tested it on case hospital data. [PERSON] et al. [16] considered the scheduling problem of patients at a lower level to minimize the overtime costs, makespan, and completion time costs of surgeons considering parallel surgeries. They proposed a mixed integer programming model and constraint programming models for the scheduling problem. All the planning level decisions are interrelated, and the solution of one level influences the solution of other levels. In the literature, all these planning levels are dealt with in a hierarchical manner where the output solution of one planning level is moved to the next lower planning level as input. All three decision levels are linked to each other so that decisions made at the strategic level influence the quality of decisions made at the tactical level. Both the higher-level decisions influence further operational-level decisions. Such interdependence of these decision levels provides the basis for research to investigate all these levels concurrently and solve the problem of multi-level planning and scheduling. Some researchers have focused on multi-level planning in healthcare facilities. For example, [PERSON] and [PERSON] [17] investigated all levels of decision-making, such as case mix planning, master surgery scheduling, and patient sequencing, at the operational level in a hierarchical manner. All three planning levels were integrated iteratively in three phases with different objective functions for each phase. In addition, [PERSON] [18] integrated higher-level planning and medium-level planning decisions. They proposed a method to calculate the distribution of patient demand in downstream departments and a model to generate a master surgery schedule with an assumption of fixed capacities. [PERSON] and [PERSON] [19] studied planning and scheduling problems at medium and lower levels. They proposed an algorithm for allocating operating rooms to specialty groups for a pre-determined period and scheduling patients in the allocated operating rooms. They developed a cyclic master surgery schedule where the patients were allocated to operating rooms based on the developed master surgery schedule. Reviewing the literature on operating room planning and scheduling shows that the importance of all levels of decision-making can be inferred. In the literature, however, when efforts to integrate any of two or three levels are made, and integration occurs in a hierarchical manner, it proceeds that the results of one planning level are used to make decisions at the lower planning level. Hierarchically, the quality of decisions made at the lower level is greatly determined and influenced by the higher-level decisions. All levels' performance can be increased if all decision-making levels are integrated.