Data-driven modeling for designing a sustainable and efficient vaccine supply chain: A COVID-19 case study

Authors

Bahareh Kargar, Newark College of Engineering
Pedram MohajerAnsari, Clemson University College of Engineering, Computing and Applied Sciences
Esra Büyüktahtakın, Newark College of Engineering
Hamed Jahani, College of Business and Law
Sri Talluri, Broad College of Business

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