Optimising vaccines supply chains to mitigate the COVID-19 pandemic

A vaccination campaign is one of the most important initiatives to return life to normal in the face of the current COVID-19 epidemic. A successful immunisation programme requires optimising the strategy since uncertainty and disruptions play a role in the decision-making process. Despite the significance of this issue in practical terms, little research has been done to develop the best vaccine delivery strategy while considering uncertainties and interruptions. By developing bi-objective mathematical models that take into account both long-term (such as the allocation of vaccine types, the size of the vaccine centre, and the number of healthcare workers per vaccine centre) and short-term (such as daily order placement) decisions, we investigate the vaccine distribution problem for Canberra city in the Australian Capital Territory. The models also consider vaccination effectiveness and hesitation, disruptions in vaccine supplies, unpredictability in vaccine transportation, and loss of vaccines while handling them. Two meta-heuristic methods are created and put into use to solve these models. The effectiveness of the suggested algorithms is assessed using self-generated examples that were motivated by actual issues. The findings of this study will aid decision-makers in streamlining COVID-19 vaccine supply chains in the face of unpredictability and disruptions.

Automated summary

This study investigates the vaccine distribution problem in Canberra, Australia by using bi-objective mathematical models that consider uncertainties and disruptions. The findings will aid decision-makers in streamlining the COVID-19 vaccine supply chains.