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Multiple Travelling Salesman Problem is a complex problem in which route for a salesman is assigned to visit a city that has various hurdles such as congested road, damaged road, etc. In recent years biologically inspired algorithms are most widely used to solve many optimization problems. Here seed based plant propagation algorithm is applied for the multiple travelling salesman problem that is also a optimization problem, and the result is compared with a short-cut routing algorithm. The result shows that Seed based Propagation Algorithm is easy to implement since it has few parameters to be utilized and also time complexity is reduced when implemented in multiple travelling salesman problem.

Abstract-Social-based routing protocols has shown its promising capability for improving the message delivery efficiency in Delay Tolerant Networks (DTNs). The efficiency relies mostly on the quality of the aggregated social graph that has been determined by the metrics used for measuring the strength of social connections. In this paper, we have proposed an improved metrics that leads to the high-quality social graph by taking both frequency and duration of the contacts into its consideration. Furthermore, to improve the performance of the social-based message transmission, we have systematically studied the community evolution problem that has been little bit investigated in the literature. Distributed algorithms based upon our new proposed metrics have been developed in such a manner that the overlapping communities and bridge nodes (i.e., connecting nodes between communities) can be dynamically detected in the evolutionary social network. Finally, we have taken all the results above into our social-based routing design. The extensive trace-driven simulation results have shown that our routing algorithm outperforms in the existing social-based forwarding strategies significantly.