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The number of cancer cases per year is rapidly increasing worldwide. Inradiation therapy (RT), radiation from linear accelerators is used to killmalignant tumor cells. Scheduling patients for RT is difficult both due to thenumerous medical and technical constraints, and because of the stochasticinflow of patients with different urgency levels. In this paper, a ColumnGeneration (CG) approach is proposed for the RT patient scheduling problem. Themodel includes all the constraints necessary for the generated schedules towork in practice, including for example different machine compatibilities,individualized patient protocols, and multiple hospital sites. The model is thefirst to include planned interruptions in treatments due to maintenance onmachines, which is an important aspect when scheduling patients in practice, asit can create bottlenecks in the patient flow. Different methods to ensure thatthere are available resources for high priority patients at arrival arecompared, including static and dynamic time reservation. Data from IridiumNetwerk, the largest cancer center in Belgium, is used to evaluate the CGapproach. The results show that the dynamic time reservation method outperformsthe other methods used to handle uncertainty in future urgent patients. Asensitivity analysis also shows that the dynamic time reservation method isrobust to fluctuations in arrival rates. The CG approach produces schedulesthat fulfill all the medical and technical constraints posed at Iridium Netwerkwith acceptable computation times.

A Column Generation Approach for Radiation Therapy Patient Scheduling with Planned Machine Unavailability and Uncertain Future Arrivals