An Efficient Heuristic for the Traveling Salesman Problem Based on a Growing SOM-like Algorithm

  • Cristina García
  • José Alí Moreno
Conference paper


A growing self-organizing (SOM) neural network, enhanced with a local search heuristic is proposed as an efficient traveling salesman problem solver. A ring structure of processing units is evolved in time with a Kohonen type adaptation dynamics together with a simple growing rule in the number of processing units. The result is a neural network heuristic for the TSP with a computational complexity of O(n 2), comparable to other reported SOM-like networks. The tour emerging from the SOM network is enhanced by the application of a simple greedy 2-Opt local search. Experiments over a broad set of TSP instances are carried out. The experimental results show a solution accuracy equivalent to that of the best SOM based heuristics reported in the literature.


Travel Salesman Problem Travel Salesman Problem Direct Neighbor Local Search Heuristic Insertion Strategy 
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/Wien 2005

Authors and Affiliations

  • Cristina García
  • José Alí Moreno
    • 1
  1. 1.Laboratorio de Computacion Emergente, Facultades de Ciencias e IngenieriaUniversidad Central de VenezuelaVenezuela

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