A New Neural Network Approach to the Traveling Salesman Problem
This paper presents a technique that uses the Wang Recurrent Neural Network with the "Winner Takes All" principle to solve the Traveling Salesman Problem (TSP). When the Wang Neural Network presents solutions for the Assignment Problem with all constraints satisfied, the "Winner Takes All" principle is applied to the values in the Neural Network’s decision variables, with the additional constraint that the new solution must form a feasible route for the TSP. The results from this new technique are compared to other heuristics, with data from the TSPLIB (TSP Library). The 2-opt local search technique is applied to the final solutions of the proposed technique and shows a considerable improvement of the results.
KeywordsNeural Network Assignment Problem Travel Salesman Problem Travel Salesman Problem Recurrent Neural Network
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- 1.Ahuja, R.K., Mangnanti, T.L., Orlin, J.B.: Network Flows. Prentice Hall, New Jersey (1993)Google Scholar
- 6.Liu, G., He, Y., Fang, Y., Oiu, Y.: A Novel Adaptive Search Strategy of Intensification and Diversification in Tabu Search. In: Proceedings of the IEEE International Conference on Neural Networks and Signal Processing – ICNNSP 2003, vol. 1, pp. 428–431. IEEE, Los Alamitos (2003)CrossRefGoogle Scholar