Article ID: | iaor1999976 |
Country: | United Kingdom |
Volume: | 48 |
Issue: | 9 |
Start Page Number: | 919 |
End Page Number: | 928 |
Publication Date: | Sep 1997 |
Journal: | Journal of the Operational Research Society |
Authors: | Enkawa Takao, Somhom S., Modares A. |
Keywords: | neural networks |
This work describes a new algorithm, based on a self-organising neural network approach, to solve the Travelling Salesman Problem (TSP). Firstly, various features of the available adaptive neural network algorithms for TSP are reviewed and a new algorithm is proposed. In order to investigate the performance of the algorithms, a comprehensive empirical study has been provided. The simulations, which are conducted on a series of standard data, evaluate the overall performance of this approach by comparing the results with the best known or the optimal solutions of the problems. The proposed algorithm shows significant advances in both the quality of the solution and computational effort for most of the experimental data. The deviation from the optimal solution of this algorithm was, in the worst case, around 2%. This fact indicates that the self-organising neural network may be regarded as a promising heuristic approach for optimisation problems.