Approximate dynamic programming modeling for a typical blood platelet bank

• It addresses some of the literature gaps and overcome curse of dimension problem.
• The model considers eight blood types with stochastic demand, stochastic supply.
• It uses news vendor model and the current inventory to control the supply uncertainty.
• It uses linear programing to solve the single-period inventory model optimally.
• It uses ADP to solve the multi-period model without any downsizing.

This paper introduces a workable model for the establishment of an inventory bank holding perishable blood platelets with a short shelf life. The model considers a blood platelet bank with eight blood types, stochastic demand, stochastic supply, and deterministic lead time. The model is formulated using approximate dynamic programming. The model is evaluated in terms of four measures of effectiveness: blood platelet shortage, outdating, inventory level, and reward gained. Moreover, several alternative inventory control policies are analyzed. The order quantity decision is taken using a news-vendor model. In addition, the variation of the O− percentage is studied. This study confirms that the blood platelet bank reward can be maximized by operating at the optimal inventory level, thereby minimizing the number of outdated units as well as shortages. In addition, the suitable O− percentage within the blood platelet bank inventory was studied. As the O− blood type inventory levels increase to 40%, shortages drop from 3.9% to 1.5%. Outdated units drop from 4.6% to 1.8%. Furthermore, when the order quantity is received twice a day, shortages drop to 1.8% and outdated units drop to 2.1%.