A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines

Eugenia Ama Andoh and Hao Yu ()
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Eugenia Ama Andoh: UiT The Arctic University of Norway
Hao Yu: UiT The Arctic University of Norway

Annals of Operations Research, 2023, vol. 328, issue 1, No 4, 75-105

Abstract: Abstract The COVID-19 pandemic has become a global health and humanitarian crisis that catastrophically affects many industries. To control the disease spread and restore normal lives, mass vaccination is considered the most effective way. However, the sustainable last-mile cold chain logistics operations of COVID-19 vaccines is a complex short-term planning problem that faces many practical challenges, e.g., low-temperature storage and transportation, supply uncertainty at the early stage, etc. To tackle these challenges, a two-stage decision-support approach is proposed in this paper, which integrates both route optimization and advanced simulation to improve the sustainable performance of last-mile vaccine cold chain logistics operations. Through a real-world case study in Norway during December 2020 and March 2021, the analytical results revealed that the logistics network structure, fleet size, and the composition of heterogeneous vehicles might yield significant impacts on the service level, transportation cost, and CO2 emissions of last-mile vaccine cold chain logistics operations.

Keywords: Sustainable logistics; Green transportation; Vaccine logistics; Cold chain logistics; COVID-19 vaccines; Simulation (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10479-022-04906-x

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