Novel Mathematical Programming Models for Radiotherapy Appointments Scheduling

A large number of cancer patients at present and the prediction of a significant increase in the number of cancer cases in the next two decades, have raised the importance of proper timing for optimal use of medical resources to cure. The radiotherapy (RT) treatment, as the most used cancer therapy, should be scheduled in several radiation sessions, with specific intervals and duration planned by the oncologists, distinguishing it from other patient scheduling issues. Our main objective is to minimize the waiting time for access to radiation care for cancer treatment. In this study, we propose a mixed integer linear programming (MILP) model to formulate the problem of scheduling and sequencing RT sessions considering current restrictions in radiotherapy centers such as treatment deadlines, patient priorities, linac capacity, and patient treatment plans. A novel feature of the proposed model is the ability to adapt any sequence of appointments prescribed for different medical conditions and the rules of medical centers. This model can simplify implementation and improve real-time scheduling, especially for cases with long queues. The results show that the model can reduce patients’ waiting time significantly according to their priorities.