The current universally challenging SARS-COV-2 pandemic has transcended all the social, logical, economic, and mortal boundaries regarding global operations. Although myriad global societies tried to address this issue, most of the employed efforts seem superficial and failed to deal with the problem, especially in the healthcare sector. On the other hand, the Internet of Things (IoT) has enabled healthcare system for both better understanding of the patient’s condition and appropriate monitoring in a remote fashion. However, there has always been a gap for utilizing this approach on the healthcare system especially in agitated condition of the pandemics. Therefore, in this study, we develop two innovative approaches to design a relief supply chain network is by using IoT to address multiple suspected cases during a pandemic like the SARS-COV-2 outbreak. The first approach (prioritizing approach) minimizes the maximum ambulances response time, while the second approach (allocating approach) minimizes the total critical response time. Each approach is validated and investigated utilizing several test problems and a real case in Iran as well. A set of efficient meta-heuristics and hybrid ones is developed to optimize the proposed models. The proposed approaches have shown their versatility in various harsh SARS-COV-2 pandemic situations being dealt with by managers. Finally, we compare the two proposed approaches in terms of response time and route optimization using a real case study in Iran. Implementing the proposed IoT-based methodology in three consecutive weeks, the results showed 35.54% decrease in the number of confirmed cases.

当前具有普遍挑战性的 SARS-COV-2 大流行已经超越了全球运营的所有社会、逻辑、经济和死亡界限。尽管无数的全球社会都试图解决这个问题，但大多数所采用的努力似乎都是肤浅的，未能解决这个问题，尤其是在医疗保健领域。另一方面，物联网 (IoT) 使医疗保健系统能够更好地了解患者的状况并以远程方式进行适当的监控。然而，在医疗保健系统中使用这种方法一直存在差距，尤其是在大流行病激增的情况下。因此，在本研究中，我们开发了两种创新方法来设计救援供应链网络，即使用物联网解决 SARS-COV-2 等大流行期间的多个疑似病例。第一种方法（优先排序方法）最小化救护车的最大响应时间，而第二种方法（分配方法）最小化总的关键响应时间。每种方法都通过几个测试问题和伊朗的真实案例进行了验证和调查。开发了一组有效的元启发式和混合启发式来优化所提出的模型。拟议的方法已经显示出它们在管理人员正在处理的各种严酷的 SARS-COV-2 大流行情况下的多功能性。最后，我们使用伊朗的真实案例研究在响应时间和路线优化方面比较了两种提出的方​​法。