A New Neural Network Approach to the Traveling Salesman Problem

  • Paulo Henrique Siqueira
  • Sérgio Scheer
  • Maria Teresinha Arns Steiner
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3971)


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.


Neural Network Assignment Problem Travel Salesman Problem Travel Salesman Problem Recurrent Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Paulo Henrique Siqueira
    • 1
  • Sérgio Scheer
    • 2
  • Maria Teresinha Arns Steiner
    • 3
  1. 1.Department of DrawingFederal University of ParanáCuritibaBrazil
  2. 2.Department of Civil ConstructionFederal University of ParanáCuritibaBrazil
  3. 3.Department of MathematicsFederal University of ParanáCuritibaBrazil

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