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GOALI: Improving Blood Collection, Production, and Inventory Operations

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:
$36.0万
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
项目状态:
已结题
起止时间:
2014-05-15 至 2017-04-30

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中文摘要
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英文摘要
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.
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RAPID: Collaborative Research: Mitigation and Suppression of Coronavirus Pandemic with Data-driven RAPID Decisions Using COVID-19 Simulator
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  • 资助金额:
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  • 财政年份:
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CAREER: Optimal Management of Chronic Diseases Caused by Infections
  • 批准号:
    1452999
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  • 资助金额:
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  • 财政年份:
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国内基金
海外基金
Improving modelling of compact binary evolution.
  • 批准号:
    10903001
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2009
  • 负责人:
    史蒂芬
  • 依托单位: