Carleton University
Technical Report TR-00-07
October 2000
A Kohonen-like Decomposition Method for the Euclidean Traveling Salesman Problem – KNIES_DECOMPOSE*
Abstract
In addition to the classical heuristic algorithms of operations research there have also been several approaches based on arti cial neural networks for solving the traveling salesman problem. Their eciency, however, decreases as the problem size (number of cities) increases. A technique to reduce the complexity of a large-scale TSP instance is to decompose or partition it into smaller subproblems. In this paper we introduce an all-neural decomposition heuristic that is based on a recent self-organizing map called KNIES, which has been successfully implemented for solving both the Euclidean traveling salesman problem (TSP) and the Euclidean Hamiltonian path problem (HPP). Our solution for the TSP proceeds by solving the HPP for the subproblems, and then patching these solutions together. No such solution has ever been reported.