Data-driven modeling for designing a sustainable and efficient vaccine supply chain: A COVID-19 case study
Document Type
Article
Publication Date
4-1-2024
Abstract
We present an agent-based simulation-optimization modeling framework to determine the optimal location of warehouses for the distribution of vaccines. We first extend an agent-based epidemiological simulation model of COVID-19 to capture disease transmission and forecast the number of susceptible individuals and infections. We then develop a sustainable VSC considering the impact of greenhouse gases and integrate the simulation model into the VSC model to minimize total costs and environmental impacts. We validate our proposed model using a real-world COVID-19 VSC in the US. Our findings underscore the importance of strategically managing vaccine supplies to control COVID-19 and other infectious outbreaks.
Identifier
85188525711 (Scopus)
Publication Title
Transportation Research Part E: Logistics and Transportation Review
External Full Text Location
https://doi.org/10.1016/j.tre.2024.103494
ISSN
13665545
Volume
184
Recommended Citation
Kargar, Bahareh; MohajerAnsari, Pedram; Esra Büyüktahtakın; Jahani, Hamed; and Talluri, Sri, "Data-driven modeling for designing a sustainable and efficient vaccine supply chain: A COVID-19 case study" (2024). Faculty Publications. 524.
https://digitalcommons.njit.edu/fac_pubs/524
