Rule-based scheduling policies for blood component production

Blood units collected from healthy donors are separated into components at dedicated facilities such as blood centres and hospitals. Despite its relevance in health care, blood supply chain research has not resulted in a straightforward methodology for scheduling blood component production. This process, which combines the challenges of managing a perishable resource with the need for high-throughput operations, requires advanced scheduling methodologies due to its computational complexity. In prior work, we developed an ILP model to optimally schedule the separation operations. While the model produced high-quality schedules and enabled extensive analysis, it required long computational times. In this context, we now propose a set of rule-based scheduling policies to generate implementable solutions fast. These solutions explicitly account for both machine processing times and the manual tasks performed by human operators at the start and completion of each operation. The objectives are to generate high-quality schedules within reduced computational times and to define practical decision-making policies for operators, thereby providing actionable insights into the production process. The proposed approach was validated using a real-life case study at Niguarda Hospital, Milan, Italy. Results show good-quality schedules with substantially reduced computational time. The rule-based policies offer clear operational guidance, enabling more informed decision-making.