The number of new cancer cases is expected to increase by about 50 % over the next 20 years, and the need for chemotherapy treatments will increase accordingly. Treatments are usually provided in outpatient cancer centers, where patients with various types of cancers receive care. The treatment delivery must be carefully planned to optimize the use of limited resources, such as consultation and examination rooms, chairs and beds for the drug infusion, medical and nursing staff. The planning and scheduling of chemotherapy treatments involve different problems at different decision levels. In this work, we focus on the operational level and jointly address the interday and intraday multi-appointment scheduling problem. We determine the day and start time of the oncologist visit and drug infusion for a set of patients to be scheduled along a short-term planning horizon. We use a per-pathology policy, where the days of the week on which patients can be treated, depending on their pathology, are known. We consider different metrics that take into account the perspectives of both the cancer center and the patients. We formulate the problem as a multi-objective optimization problem, which is tackled by sequentially solving three problems in a lexicographic multi-objective fashion. The problems turn out to be computationally challenging; thus, we propose ad hoc decomposition approaches. The approaches are tested on real data from an Italian hospital and improve upon state-of-the-art solvers.

This abstract was taken from the following paper: Carello G., Passacantando M., Tanfani E. (in press), Interday and Intraday Chemotherapy Appointment Scheduling: a Patient-Centered Approach, European Journal of Operational Research, DOI: 10.1016/j.ejor.2025.12.023.