Utilizing IoT to design a relief supply chain network for the SARS-COV-2 pandemic

Abstract

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.

Is artificial intelligence an enabler of supply chain resiliency post COVID-19? An exploratory state-of-the-art review for future research

“…A multi-objective optimization model was proposed to enable a sustainable supply chain network design under uncertainty by using strength Pareto evolutionary algorithm 2 (SPEA2) (Hasani et al 2021 ). Zahedi et al ( 2021 ) developed a relief supply chain network using the internet of things (IoT) to analyse several suspected cases during the pandemic. Mehar approach was suggested to solve the distance problem in the supply chain network, by using the lexicographic method to compare interval-valued Pythagorean fuzzy numbers (Bhatia et al 2021 ).…”

Digital Technology-Based Telemedicine for the COVID-19 Pandemic

“…Community residents with respiratory symptoms, which might be early signs of COVID-19, could consult using the online clinic consultation services. Srinivasa Rao et al ( 52 ) and Zahedi et al ( 53 ) provided frameworks ( Figures 4A–C ) based on AI algorithm and IoT that could enable quick identification of COVID-19 cases, by performing risk assessment on the symptoms and signs associated with this novel coronavirus though web- and mobile-based survey, respectively. And, depending on the replies, this algorithm could send alerts to the respondent, as well as to clinics or the mobile health units, for further health visits and case confirmation.…”

Disaster relief supply chain design for personal protection equipment during the COVID-19 pandemic

“…Regarding the pandemic disruptions in the SC sector and mitigating severe and harmful impacts on different supply chains, researchers and scholars sought the presence of supply chains that can cope with the unpleasant troubles and problems in this field. As we elaborately discuss recent studies in the supply chain in following, they encompass a variety of subjects such as supply chain design [21] , [22] , forecasting and planning [23] , supply management [24] , [25] , transportation and logistics management [26] , [27] .…”

“…Generally, these algorithms are to find an optimal solution between two or more conflicting objectives. The weighted sum approach is a famous solution approach in a multi-objective perspective [22] , [62] , [63] , [64] . Under this method, initially, all the objectives are converted to single-objective by assigning some weight, making it easier to apply traditional algorithms.…”