Solution of Cluster Traveling Salesman Problem using Heuristic Based Genetic Algorithm with Risk Constraint

Abstract

This is a heuristic investigation with risk constraint for solving the traveling salesman problem (TSP) dividing given vertices (nodes) between a prespecified number of clusters. A Heuristic based Genetic Algorithm (HbGA) is applied on each cluster to produce a Hamiltonian path based on prespecified nodes of a cluster. Each cluster must have a unique set of nodes. Finally, all Hamiltonian path of each cluster together prepare a possible Hamiltonian cycle. The efficiency of our proposed algorithm has been tested for a number of symmetric TSPLIB instances of various sizes. The computational results show the proposed algorithm works well in realistic manner.