Scheduling of chemotherapy drugs preparation : an approximation approach

The timely preparation of chemotherapy drugs is critical for ensuring effective and safe cancer treatment. Hospital pharmacies must balance patient waiting times with material costs under strict resource constraints. We address this challenge through a parallel-machine scheduling problem with release dates, incorporating pharmaceutical-specific features such as vial reuse, drug stability and technician availability. To our knowledge, these factors have not been jointly addressed in previous scheduling models at the scale of an entire cancer center. We propose a hybrid solution approach that combines a Mixed Integer Programming (MIP) formulation with a list algorithm reconstruction procedure. The MIP assigns prescriptions to time windows rather than fixed start times, allowing the reconstruction algorithm to generate feasible and implementable daily schedules. This design substantially reduces computation time while maintaining high solution quality. Extensive experiments on real data from a Quebec cancer center demonstrate that the proposed approach produces high-quality schedules, reducing maximum patient tardiness by up to 12% and material costs by over 1.4% compared with current hospital practice. These results highlight the method’s potential as a practical decision-support tool for hospital pharmacies.