  This paper attempts to solve the famous Vehicle Routing Problem by
considering multiple constraints including capacitated vehicles, single depot,
and distance using two approaches namely, cluster first and route the second
algorithm and using integer linear programming. A set of nodes are provided as
input to the system and a feasible route is generated as output, giving
clusters of nodes and the route to be traveled within the cluster. For
clustering the nodes, we have adopted the DBSCAN algorithm, and the routing is
done using the approximation algorithm, Christofide's algorithm. The solution
generated can be employed for solving real-life situations, like delivery
systems consisting of various demand nodes.
