A model of supply-chain decisions for resource sharing with an application to ventilator allocation to combat COVID-19.

IF 1.9 4区 管理学 Q3 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Naval Research Logistics Pub Date : 2020-08-01 Epub Date: 2020-05-02 DOI:10.1002/nav.21905
Sanjay Mehrotra, Hamed Rahimian, Masoud Barah, Fengqiao Luo, Karolina Schantz
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Abstract

We present a stochastic optimization model for allocating and sharing a critical resource in the case of a pandemic. The demand for different entities peaks at different times, and an initial inventory for a central agency are to be allocated. The entities (states) may share the critical resource with a different state under a risk-averse condition. The model is applied to study the allocation of ventilator inventory in the COVID-19 pandemic by FEMA to different U.S. states. Findings suggest that if less than 60% of the ventilator inventory is available for non-COVID-19 patients, FEMA's stockpile of 20 000 ventilators (as of March 23, 2020) would be nearly adequate to meet the projected needs in slightly above average demand scenarios. However, when more than 75% of the available ventilator inventory must be reserved for non-COVID-19 patients, various degrees of shortfall are expected. In a severe case, where the demand is concentrated in the top-most quartile of the forecast confidence interval and states are not willing to share their stockpile of ventilators, the total shortfall over the planning horizon (until May 31, 2020) is about 232 000 ventilator days, with a peak shortfall of 17 200 ventilators on April 19, 2020. Results are also reported for a worst-case where the demand is at the upper limit of the 95% confidence interval. An important finding of this study is that a central agency (FEMA) can act as a coordinator for sharing critical resources that are in short supply over time to add efficiency in the system. Moreover, through properly managing risk-aversion of different entities (states) additional efficiency can be gained. An additional implication is that ramping up production early in the planning cycle allows to reduce shortfall significantly. An optimal timing of this production ramp-up consideration can be based on a cost-benefit analysis.

资源共享供应链决策模型,应用于呼吸机分配以对抗 COVID-19。
我们提出了一个在大流行病情况下分配和共享关键资源的随机优化模型。不同实体的需求在不同时间达到峰值,中央机构的初始库存需要分配。各实体(州)可在规避风险的条件下与不同州共享关键资源。该模型被用于研究美国联邦紧急事务管理局在 COVID-19 大流行中向美国各州分配呼吸机库存的情况。研究结果表明,如果不到 60% 的呼吸机库存可用于非 COVID-19 病人,那么联邦紧急事务管理局的 20,000 台呼吸机库存(截至 2020 年 3 月 23 日)几乎足以满足略高于平均需求情况下的预计需求。然而,当超过 75% 的可用呼吸机库存必须留给非 COVID-19 患者时,预计会出现不同程度的短缺。在最严重的情况下,即需求集中在预测置信区间的最上四分位数,且各州不愿意分享其库存呼吸机时,规划期内(至 2020 年 5 月 31 日)的总短缺量约为 232 000 个呼吸机日,2020 年 4 月 19 日的高峰短缺量为 17 200 个呼吸机日。此外,还报告了需求量达到 95% 置信区间上限的最坏情况下的结果。本研究的一个重要发现是,中央机构(联邦紧急事务管理局)可以充当协调者,共享长期短缺的关键资源,以提高系统效率。此外,通过对不同实体(州)的风险规避进行适当管理,还可以提高效率。另一个意义在于,在计划周期的早期提高产量可以显著减少短缺。可以根据成本效益分析来确定提高产量的最佳时机。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Naval Research Logistics
Naval Research Logistics 管理科学-运筹学与管理科学
CiteScore
4.20
自引率
4.30%
发文量
47
审稿时长
8 months
期刊介绍: Submissions that are most appropriate for NRL are papers addressing modeling and analysis of problems motivated by real-world applications; major methodological advances in operations research and applied statistics; and expository or survey pieces of lasting value. Areas represented include (but are not limited to) probability, statistics, simulation, optimization, game theory, quality, scheduling, reliability, maintenance, supply chain, decision analysis, and combat models. Special issues devoted to a single topic are published occasionally, and proposals for special issues are welcomed by the Editorial Board.
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