Linear Programming and Network Flows
Linear Programming and Network Flows
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 assignment networks
IEEE Transactions on Neural Networks
A New Hybrid Ant Colony Optimization Algorithm for the Traveling Salesman Problem
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Expert Systems with Applications: An International Journal
Solving TSP by using Lotka-Volterra neural networks
Neurocomputing
Honey bees mating optimization algorithm for the Euclidean traveling salesman problem
Information Sciences: an International Journal
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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 (SOM, SA and heuristics of remotion and insertion of arcs), with data from the traveling salesman problem library (TSPLIB). The 2-opt local search technique is applied to the final solutions of the proposed technique and shows a considerable improvement of the results. The advantages of this new technique are the easy computational implementation, the low computational complexity, the good results obtained and the possibility of solving symmetrical and asymmetrical problems with the same technique.