Solution of Cluster Traveling Salesman Problem using Heuristic Based Genetic Algorithm with Risk Constraint
Arindam Roy
Arindam Roy, Dept. of Computer Sc. and App., Prabhat Kumar College, Contai ,WB, India.
Manuscript received on November 11, 2019. | Revised Manuscript received on 23 November, 2019. | Manuscript published on December 10, 2019. | PP: 2523-2526 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7119129219/2019©BEIESP | DOI: 10.35940/ijitee.B7119.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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.
Keywords: Cluster TSP, HbGA, Heuristic.
Scope of the Article: Algorithm Engineering