Ant colony system with communication strategies
Information Sciences—Informatics and Computer Science: An International Journal
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
An efficient self-organizing map designed by genetic algorithms for the traveling salesman problem
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Primal and dual neural networks for shortest-path routing
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Primal and dual assignment networks
IEEE Transactions on Neural Networks
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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.