Integrated scheduling and perishable inventory for chemotherapy drug preparation under cancellation uncertainty

The preparation of chemotherapy drugs in hospital pharmacies involves complex operational decisions due to patient-specific prescriptions, perishable materials, and frequent last-minute cancellations. Pharmacy managers must balance early preparation to avoid treatment delays against the risk of drug waste. Despite its importance, this problem has received limited attention, and existing approaches typically consider scheduling and inventory decisions separately. We model the chemotherapy drug preparation problem as a two-stage stochastic program integrating parallel machine scheduling, batching decisions, and perishable inventory management. The formulation captures key operational features, including drug stability, vial reuse, technician availability, and patient cancellations. To address the resulting large-scale problem, we develop a solution approach based on a mixed-integer approximation and a reconstruction heuristic. Computational experiments on real-world instances from a cancer center in Quebec show that the proposed method significantly reduces both tardiness and material costs compared to current practices. The results highlight the value of jointly optimizing batching and anticipation decisions under uncertainty.