GOALI: Improving Blood Collection, Production, and Inventory Operations

目标：改善血液采集、生产和库存运营

• 批准号: 1335137
• 负责人: Turgay Ayer
• 金额: $ 36万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-05-15 至 2017-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1335137&HistoricalAwards=false
• 关键词: GOALI; Improving; Blood; Collection; Production

The objectives of this Grant Opportunity for Academic Liaison with Industry (GOALI) award are: (1) to develop and analyze mathematical and computational models of key elements of the blood products collection, production, and inventory system at a large regional level in order to improve the overall system performance and (2) to advance the state of knowledge in the analysis of these models. The methods that will be used and extended include: completely observed and partially observed Markov decision processes (MDPs) and Markov games, chance constrained MDPs, artificial intelligence-based heuristic search algorithms, mathematical programming, exact and approximate dynamic programming, and stochastic programming. In collaboration with the American Red Cross (ARC), a comprehensive decision support system (DSS) based on proposed models and algorithms will be built. The outcomes of this DSS will be tested for validation in real collection, production, and inventory environments at the ARC production facility, and at hospitals and blood banks in the region.This research is intended to directly impact the quality of delivery in 120 regional hospitals and health facilities and hence can potentially affect millions of people in the Southeast United States. If successful, this research will lead to a more cost-effective blood products collection, production, and inventory system with fewer blood product unit stock outs and with a reduced number of blood product units exceeding their lifetime. Furthermore, the models and decision support tools developed as part of these projects may ultimately be adapted by other service regions in the United States.

该奖学金的目标是：(1)在大区域层面开发和分析血液制品收集、生产和库存系统关键要素的数学和计算模型，以改善整体系统性能；(2)在分析这些模型时提高知识水平。将使用和扩展的方法包括：完全观察和部分观察马尔可夫决策过程（mdp）和马尔可夫博弈，机会约束mdp，基于人工智能的启发式搜索算法，数学规划，精确和近似动态规划以及随机规划。与美国红十字会（ARC）合作，将建立一个基于拟议模型和算法的综合决策支持系统（DSS）。将在ARC生产设施以及该区域的医院和血库的实际收集、生产和库存环境中对该决策支持系统的结果进行验证。这项研究的目的是直接影响120家地区医院和卫生设施的分娩质量，因此可能会影响到美国东南部数百万人。如果取得成功，这项研究将导致一个更具成本效益的血液制品收集、生产和库存系统，减少血液制品单位缺货，减少超过其使用寿命的血液制品单位数量。此外，作为这些项目的一部分开发的模型和决策支持工具最终可能被美国的其他服务区域采用。