Tabu Search Algorithm for the Near-Optimal Order Quantity of Blood Inventory

Abstract

Blood is critical product needed for transfusions to save lives. Blood inventory is a perishable. The shortage of blood results to loss of life. Overstock results in high costs and product expiration. Tabu search (TS) is the method to find near-optimal order quantity when the unit of blood stock is lower than safety stock. At reorder point, we place the order of blood units from Blood service center and/or obtain donation. We formulation a model by considering the safety stock and reorder point. The objective is to minimize the expected total cost as reducing shortage blood units. We compare the results of our algorithm using TS with given safety stock and reorder point (NO-TS-STROP), our TS with no given safety stock and reorder point (NO-TS), and the current method with no given safety stock and reorder point (CM). We investigate the model using real-world data which collect from Suranaree University of Technology Hospital (SUTH). The numerical results show that the NO-TS-STROP provides better result of the expected total cost, reduces shortage blood units and reduces loss blood unit than other policies.