Affiliations: [a] Department of Management Engineering, School of Economics & Management, Xidian University, Xi’an, China
| [b] Department of Pathology, State Key Laboratory of Cancer Biology, Xijing Hospital and School of Basic Medicine, Fourth Military Medical University, Xi’an, China
Correspondence:
[*]
Corresponding author. Xia Li, Department of Pathology, State Key Laboratory of Cancer Biology, Xijing Hospital and School of Basic Medicine, Fourth Military Medical University, Xi’an 710032, China. E-mail: [email protected].
Abstract: Rh-negative rare blood inventory protection plays an important role in emergency blood protection. Normally, hospitals typically hold a fixed amount of daily reserve in response to emergency needs, but the measure can increase the unnecessary cost of repeated freezing and thawing. In order to save manpower, protect blood resources and reduce costs, a two-stage stochastic model is proposed to determine the optimal daily reserve of Rh-negative red blood cells, taking into account the uncertainty of demand. First, the model focuses on minimizing operational cost, shortage cost and damage caused by blood substitution. Then, the proposed model generates a series of discrete scenarios to solve the uncertainty of demand and predict the demand. In addition, a case study is presented to prove the validity of the proposed model with real data. Sensitivity analysis is also established to observe the effect of parameter changes on the results. Finally, the results show that the proposed model can effectively reduce the cost and current waste.
Keywords: Rh-negative, red blood cells, inventory management, stochastic demand, two-stage stochastic model
