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Evolving Strategies for Updating Pheromone Trails: A Case Study with the TSP

  • Jorge Tavares
  • Francisco B. Pereira
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6239)

Abstract

Ant Colony Optimization is a bio-inspired technique that can be applied to solve hard optimization problems. A key issue is how to design the communication mechanism between ants that allows them to effectively solve a problem. We propose a novel approach to this issue by evolving the current pheromone trail update methods. Results obtained with the TSP show that the evolved strategies perform well and exhibit a good generalization capability when applied to larger instances.

Keywords

Particle Swarm Optimization Travel Salesman Problem Pheromone Trail Genetic Program Algorithm Good Generalization Capability 
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 2010

Authors and Affiliations

  • Jorge Tavares
    • 1
  • Francisco B. Pereira
    • 1
    • 2
  1. 1.CISUC, Department of Informatics EngineeringUniversity of Coimbra
  2. 2.Polo II - Pinhal de Marrocos, 3030 Coimbra, PortugalISEC, Quinta da NoraCoimbraPortugal

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