A simulation-driven (r, Q) replenishment policy for perishable blood inventory management

Effective blood inventory management is necessary for sustaining appropriate supply levels and reducing costs, particularly given the blood products perishable nature alongside the demand uncertainty. This study employs the (r, Q) replenishment policy as a robust and easily implementable method for hospitals intern blood banks. Therefore, we formulate a modular simulation approach that engenders replenishment orders predicated on reorder point r and order quantity Q, while taking into consideration the variable shelf lives and demand variability. Thus, numerical experiments reveal that the (r, Q) policy standardizes ordering decisions by shifting away from purely ad-hoc demands, minimizes both stockout and spoilage costs compared to “order-on-demand” approaches, and adjustable to hospital specific metrics and comprehensible to medical staff with limited supply chain expertise. These insights emphasize the practical significance of the (r, Q) approach for perishable blood products and propose strategic assistance for its application in healthcare logistics.