Notice of RetractionClustering process to solve euclidean TSP

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Human is able to cluster and filter object efficiently. Clustering problem has been approached from diverse domains of knowledge like graph theory, statistics, artificial neural network and so on. There has been growing interest in studying combinatorial optimization problems by clustering approach, with a special emphasis on the Euclidean Traveling Salesman Problem. Classical ETSP appears as a fundamental problem in various problem such as transportation, manufacturing and logistics application. This study will focus on tour construction. Most of methods focus on tour improvement and using nearest neighborhood for tour construction. This paper will use clustering process to decompose ETSP into smaller sub problem. Clustering process hierarchically arrange adjacency and vertices to form clusters. A threshold of edge weight is applied to split one clusters to several sub clusters. Using this approach the running time can be cut into half compared to TSPLib standard time. The main objective is to develop best clustering process to ETSP and produce a near optimal solution within 10% of best known solution in TSPLib.