This paper deals with generating of an optimized route for multiple Vehicle
routing Problems (mVRP). We used a methodology of clustering the given cities
depending upon the number of vehicles and each cluster is allotted to a
vehicle. k- Means clustering algorithm has been used for easy clustering of the
cities. In this way the mVRP has been converted into VRP which is simple in
computation compared to mVRP. After clustering, an optimized route is generated
for each vehicle in its allotted cluster. Once the clustering had been done and
after the cities were allocated to the various vehicles, each cluster/tour was
taken as an individual Vehicle Routing problem and the steps of Genetic
Algorithm were applied to the cluster and iterated to obtain the most optimal
value of the distance after convergence takes place. After the application of
the various heuristic techniques, it was found that the Genetic algorithm gave
a better result and a more optimal tour for mVRPs in short computational time
than other Algorithms due to the extensive search and constructive nature of
the algorithm.