ArticleApplied soft computing2021
Utilizing IoT to design a relief supply chain network for the SARS-COV-2 pandemic.
Article in Applied soft computing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Emergency medical service interventions and experiences during pandemics: A scoping review.PloS one · 2024Article
- Designing a new sustainable Test Kit supply chain network utilizing Internet of Things.Engineering applications of artificial intelligence · 2023Article
- Innovation in humanitarian logistics and supply chain management: a systematic review.Annals of operations research · 2023Article
- A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study.Socio-economic planning sciences · 2023Article
- Green Closed-Loop Supply Chain Network Design During the Coronavirus (COVID-19) Pandemic: a Case Study in the Iranian Automotive Industry.Environmental modeling and assessment · 2023Article
- Designing humanitarian logistics network for managing epidemic outbreaks in disasters using Internet-of-Things. A case study: An earthquake in Salas-e-Babajani city.Computers & industrial engineering · 2023Article
- Blood plasma supply chain planning to respond COVID-19 pandemic: a case study.Environment, development and sustainability · 2022Article
- A review of recent advances in quantum-inspired metaheuristics.Evolutionary intelligence · 2022Review
- Using network data envelopment analysis to assess the sustainability and resilience of healthcare supply chains in response to the COVID-19 pandemic.Annals of operations research · 2022Article
- A visual review of artificial intelligence and Industry 4.0 in healthcare.Computers & electrical engineering : an international journal · 2022Article
- A mathematical model for managing the multi-dimensional impacts of the COVID-19 pandemic in supply chain of a high-demand item.Annals of operations research · 2022Article
- Towards an efficient collection and transport of COVID-19 diagnostic specimens using genetic-based algorithms.Applied soft computing · 2022Article
- Disaster relief supply chain design for personal protection equipment during the COVID-19 pandemic.Applied soft computing · 2021Article
- Molecular scaffolds from mother nature as possible lead compounds in drug design and discovery against coronaviruses: A landscape analysis of published literature and molecular docking studies.Microbial pathogenesis · 2021Review
- Relief Supply Chain Management Using Internet of Things to Address COVID-19 Outbreak.Computers & industrial engineering · 2021Article
- An improved ant colony optimization algorithm based on context for tourism route planning.PloS one · 2021Article
- Digital Technology-Based Telemedicine for the COVID-19 Pandemic.Frontiers in medicine · 2021Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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