International audienceThis paper addresses the problem of appointment scheduling of patients of an oncology outpatient unit. Each patient is first seen by his oncologist, and then the drug is prepared and injected to the patient. Two major resources including oncologists for consultation and beds for injection are considered. Idle times of oncologists are not allowed. The problem consists in scheduling the appointment time of each patient and the starting time of the injection in order to minimize the total weighted cost incurred by patient waiting times and the makespan. A Lagrangian relaxation-based heuristic and a local optimization heuristic are proposed. Numerical results show that the Lagrangian relaxation-based heuristic always outperforms the local optimization heuristic

This paper addresses the problem of determining the work schedule, called medical planning, of oncologists for chemotherapy of oncology patients at ambulatory care units. A mixed integer programming (MIP) model is proposed for medical planning in order to best balance bed capacity requirements under capacity constraints of key resources such as beds and oncologists. The most salient feature of the MIP model is the explicit modeling of specific features of chemotherapy such as treatment protocols. The medical planning problem is proved to be NP-complete. A threestage approach is proposed for determining good medical planning in reasonable computational time.From numerical experiments based on field data, the three-stage approach takes less than 10 minutes and always outperforms the direct application of MIP solvers with 10h CPU time. Compared with the current planning, the three-stage approach reduces the peak daily bed capacity requirement by 20h to 45h while the maximum theoretical daily bed capacity is 162h.

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