COVID应对:研究大型公立大学消毒站部署的混合方法

Tyler C. OBrien, Steven Foster, Emily L. Tucker, Sudeep Hegde
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引用次数: 3

摘要

我们提出了一种混合方法,将定性人为因素和定量运筹学建模相结合,以了解克莱姆森大学如何适应新冠肺炎大流行的挑战。我们主要侧重于战略性地部署洗手站,以减少病毒的传播。我们确定危机期间各部门之间的关键调整和有效协调。我们描述了定性数据如何影响我们的离散设施位置覆盖模型的开发,并使用该模型选择加油站的最佳位置。未来的计划包括进一步的模型开发,提供模型知情的重新部署建议,为2021年秋季学期做准备,以及战术规划。混合方法可以广泛应用于理解和改进其他环境中的弹性决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COVID Response: A Blended Approach to Studying Sanitizer Station Deployment at a Large Public University
We present a blended approach to integrate qualitative human factors and quantitative operations research modeling to understand how Clemson University adapted to the challenges of the COVID-19 pandemic. We focus primarily on the strategic deployment of hand sanitizer stations to reduce transmission of the virus. We identify key adaptations and effective coordination amongst various departments during the crisis. We describe how the qualitative data influenced our development of a discrete facility location covering model and use the model to select optimal locations for dispenser stations. Future plans include further model development, providing model-informed redeployment recommendations in preparation for the Fall 2021 semester, and tactical planning. The blended approach can be broadly applied to understand and improve resiliency decisions in other contexts.
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