  With the approval of vaccines for the coronavirus disease by many countries
worldwide, most developed nations have begun, and developing nations are
gearing up for the vaccination process. This has created an urgent need to
provide a solution to optimally distribute the available vaccines once they are
received by the authorities. In this paper, we propose a clustering-based
solution to select optimal distribution centers and a Constraint Satisfaction
Problem framework to optimally distribute the vaccines taking into
consideration two factors namely priority and distance. We demonstrate the
efficiency of the proposed models using real-world data obtained from the
district of Chennai, India. The model provides the decision making authorities
with optimal distribution centers across the district and the optimal
allocation of individuals across these distribution centers with the
flexibility to accommodate a wide range of demographics.
