Joint allocation of emergency medical resources with time-lag correlation during cross-regional epidemic outbreaks
Joint allocation of emergency medical resources with time-lag correlation during cross-regional epidemic outbreaks
复制标题
跨区域疫情期间具有时滞相关性的应急医疗资源联合配置
DOI：
10.1016/j.cie.2021.107895
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发表时间：
2021-12
影响因子：
7.9
通讯作者：
Ying Sun
中科院分区：
文献类型：
--
作者：
Haiping Zhang;Wenhui Zhou;Ying Sun
·跨区域流行病时滞相关的联合分配问题。·我们开发了一种基于资源之间关系的联合分配方案。·我们将时滞相关性建模为依赖于周期的递归方程。·提出了一种基于序列解生成策略（SSGS）的算法。·我们提出的方案获得了更好的解决方案，具有更少的损失和更高的公平性。在跨区域疫情暴发期间，疑似感染患者对检测资源需求较高，确诊感染患者对治疗资源需求较高。检验资源配置影响多地区、不同时期的诊疗资源需求，具有时滞相关性。在这项研究中，我们开发了一个联合分配模型，用于分配检测和治疗资源，并考虑到它们的时滞相关性，以最大限度地减少患者的损失，并最大限度地提高各地区分配的公平性。我们设计了一个顺序的解决方案生成策略（SSGS），并结合NSGA2和MOPSO算法来解决所提出的联合分配问题。我们证明了数值NSGA2与SSGS耦合产生一个更好的解决方案。此外，我们比较了我们的联合分配模型的解决方案与一个独立的分配模型。我们的数值计算结果表明，联合分配方案，它考虑了两种类型的资源之间的时滞相关性，具有更好的性能，具有较低的病人损失和更高的公平性分配。特别是，当检测资源的分配对治疗资源需求的影响增加时，联合分配方案在两个目标方面都表现得更好。
• A joint allocation problem with time-lag correlation in cross-regional epidemics. • We develop a joint allocation scheme based on the relationship among resources. • We model the time-lag correlation as period-dependent recursive equations. • We propose a sequential solution generation strategy (SSGS) based algorithm. • Our proposed scheme obtains a better solution with less loss and higher fairness. During cross-regional epidemic outbreaks, patients with suspected infection have a high demand for testing resources, while patients with confirmed infection have a high demand for treatment resources. The allocation of testing resources affects the demand for treatment resources in multiple regions and at different periods, which features a time-lag correlation. In this study, we developed a joint allocation model for allocating testing and treatment resources with consideration of their time-lag correlation to minimize the loss of patients and maximum the fairness of allocation in all regions. We devised a sequential solution generation strategy (SSGS) and combined it with the NSGA2 and MOPSO algorithms to solve the proposed joint allocation problem. We demonstrated numerically that NSGA2 coupled with SSGS yields a better solution. Furthermore, we compared the solutions of our joint allocation model with those of an independent allocation model. Our numerical results show that the joint allocation scheme, which considers the time-lag correlation between the two types of resources, has better performance—with a lower loss of patients and higher fairness of allocation. In particular, when the impact of the allocation of testing resources on the demand for treatment resources was increased, the joint allocation scheme performed better in terms of both the objectives.
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影响因子：
6.4
作者：
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通讯作者：
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