  As the world fights to contain and control the spread of the Novel
Coronavirus, countries are imposing severe measures from restrictions on travel
and social gatherings to complete lockdowns. Lockdowns, though effective in
controlling the virus spread, leaves a massive economic impact. In a country
like India with 21.9 % of its population below the poverty line, lockdowns have
a direct impact on the livelihood of a large part of the population. Our
approach conforms to healthcare and state practices of reducing human to human
contact, by optimizing the lockdown strategy. We propose resuming economic
activities while keeping healthcare facilities from being overwhelmed. We model
the coronavirus pandemic as SEIR dynamic model for a set of states as nodes
with certain population and analyze the model output before and after complete
lockdown. Social distancing that people would willingly follow, in the no
lockdown situation is modeled as being influenced with the knowledge of the
current number of infection by imitating Granovetter threshold model. We then
provide optimal lockdown policy solutions for the duration of ten weeks using
NSGA-II optimization algorithm. While there are many studies that focus on
modelling the transmission of COVID-19, ours is one of the few attempts to
strike a balance between number of infections and economic operations.
