Balanced centroids (BC) k-means clustering algorithm to transform MTSP to TSP

Solving a multiple travelling salesperson (mTSP) is more difficult than solving a travelling salesperson. Although the TSP has received a great deal of attention, the research on the mTSP is limited. In the mTSP, the N cities must be partitioned into m tours, with each tour resulting in a TSP for one salesperson. The purpose of this paper is to review in brief the existing literature on the mTSP and to transform the most 'NP complete' problem to an ordinary TSP. We propose a technique to transform mTSP to TSP using BC k-means clustering. The methodology we mentioned here will be suitable for any type of Euclidean mTSP. The result shows that the number of iterations (NI) required to get the solution are less in BC k-means clustering in most of the cases.