A hybrid particle swarm optimization model for the traveling salesman problem

  • Thiago R. Machado
  • Heitor S. Lopes


This work presents a new hybrid model, based on Particle Swarm Optimization, Genetic Algorithms and Fast Local Search, for the symmetric blind traveling salesman problem. A detailed description of the model is provided. The implemented system was tested with instances from 76 to 2103 cities. For instances up to 439 cities, results were, in average, less than or around 1% in excess of the known optima. When considering all instances, results were 2.1498% in excess, in average. These excellent results encourage further research and improvement of the hybrid model.


Local Search Hybrid Model Travel Salesman Problem Travel Salesman Problem Activation Vector 
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

  • Thiago R. Machado
    • 1
  • Heitor S. Lopes
    • 1
  1. 1.Bioinformatics Lab./CPGEIFederal Center for Technological Education of ParanaCuritibaBrazil

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