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Particle Swarm for the Traveling Salesman Problem

  • Elizabeth F. Gouvêa Goldbarg
  • Givanaldo R. de Souza
  • Marco César Goldbarg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3906)

Abstract

This paper presents a competitive Particle Swarm Optimization algorithm for the Traveling Salesman Problem, where the velocity operator is based upon local search and path-relinking procedures. The paper proposes two versions of the algorithm, each of them utilizing a distinct local search method. The proposed heuristics are compared with other Particle Swarm Optimization algorithms presented previously for the same problem. The results are also compared with three effective algorithms for the TSP. A computational experiment with benchmark instances is reported. The results show that the method proposed in this paper finds high quality solutions and is comparable with the effective approaches presented for the TSP.

Keywords

Particle Swarm Optimization Local Search Particle Swarm Particle Swarm Optimization Algorithm Travel Salesman Problem 
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

  • Elizabeth F. Gouvêa Goldbarg
    • 1
  • Givanaldo R. de Souza
    • 1
  • Marco César Goldbarg
    • 1
  1. 1.Department of Informatics and Applied MathematicsFederal University of Rio Grande do NorteNatalBrazil

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