Capacity allocation for balancing cost and fairness in a imaging facility setting

Due to expensive procurement cost and high operating cost, Magnetic Resonance Imaging (MRI) is usually one of bottleneck resources in hospitals. As MRI is shared by multi-types of patients with different requirements of examinations, setup time is needed to change coil between different patient types. Therefore, the same type patients are arranged in a sequential order to reduce setup time. This paper proposes an integer linear programming model based on a long sample path of patient arrivals for optimizing the capacity allocation. The problem consists in determining the amount of capacity allocates to each type with the objective of balancing total cost and medical service fairness. Numerical experiments with various machine daily working time and setup time are performed to show the efficiency of the proposed approach and demonstrate that the proposed capacity allocation solution is better than the widely used capacity pooling solution.