A New Model for Blood Inventory Management

血液供应的有效管理具有重要的经济和社会意义，因为在许多国家，血液产品的需求增长速度快于献血[2]。到目前为止，这一领域的大量研究都将问题建模为排队或库存系统，并使用经典的运筹学工具，如随机过程、动态规划和随机规划来解决问题。为了使模型易于理解，大多数论文简化了血液产品供应链的基本要素，例如系统的多级结构(即区域中心和个别医院的库存持有量)、血液产品的可替代性(例如接受O+而不是A+血液产品类型)、患者的可变需求量、患者状态随时间变化的可能性(即从非紧急到紧急)、为满足未来紧急需求而对血液供应的多级配给。以及产品链梯队之间的运输时间(例如，从区域库存到单个医院库存之间)及其对剩余血液产品寿命的影响。**最近，Abouee-Mehrizi等人。[1]引入了一种名为“客户组合”的新方法，解决了单级和多级库存管理中的几个已知问题，包括多级M/G/1按库存生产系统的多级配给[1]和具有随机生产和运输时间的多级库存管理中的优先级问题[2]。他们还表明，与动态规划不同，客户构成不受维度诅咒的影响。**基于将客户构成方法应用于血库的初步结果，并以单位流量法[6]和流体配方[24]补充该方法，建议的研究计划旨在解析地解决具有随机运输时间的血液产品供应链的多梯队多类别系统，该系统考虑了库存配给、患者状态的变化、可变需求量和血液产品的可替代性。

Efficient management of blood supplies is of great economic and social importance, as in many countries demand for blood products is growing faster than donations [2]. To date, the vast body of research in this area model the problem as a queuing or inventory system and use classical operations research tools such as stochastic processes, dynamic programming and stochastic programming to tackle the problem. To make the model tractable, most papers simplify the fundamental elements of the blood product supply chain, such as the multi-echelon structure of the system (i.e. inventory holdings at the regional center as well as individual hospitals), blood product substitutability (e.g. receiving O+ instead of A+ blood product type), variable demand volumes by patients, probability of change of patient status over time (i.e. from non-urgent to urgent), multi-level rationing of blood supplies to satisfy future urgent demands, and transportation time between the echelons of the product chain (e.g. from the regional stock to and among individual hospital stocks) and its impact on remaining blood product lifetime.** Recently, Abouee-Mehrizi et al. [1] introduced a new method called "customer composition" and solved several known problems in single and multi-echelon inventory management including multilevel rationing in multi-class M/G/1 make-to-stock systems [1] and prioritization in multi-echelon inventory management with stochastic production and transportation times [2]. They also showed that unlike the dynamic programming, customer composition does not suffer from the curse of dimensionality.** Building on initial results from applying the customer composition method to blood banking, and supplementing the method with the unit-flow approach [6] and fluid formulation [24], the proposed research program aims to analytically solve a multi-echelon multi-class system of blood product supply chain with stochastic transportation times that accounts for inventory rationing, changes in patient status, variable demand volumes, and blood product substitutability.********