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

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Parallel Problem Solving from Nature, PPSN XI (PPSN 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6239))

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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.

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Author information

Authors and Affiliations

  1. CISUC, Department of Informatics Engineering, University of Coimbra,  

    Jorge Tavares & Francisco B. Pereira

  2. Polo II - Pinhal de Marrocos, 3030 Coimbra, Portugal, ISEC, Quinta da Nora, 3030, Coimbra, Portugal

    Francisco B. Pereira

Authors
  1. Jorge Tavares
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  2. Francisco B. Pereira
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Editor information

Editors and Affiliations

  1. Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of ComputerScience, AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Robert Schaefer

  2. Departamento de Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Campus Teatinos, 29071, Málaga, Spain

    Carlos Cotta

  3. Department of Mathematics and Computer Science, University of Bielsko-Biala, Willowa 2, 43-309, Bielsko-Biala, Poland

    Joanna Kołodziej

  4. Fakultät für Informatik, Technische Universität Dortmund, 44221, Dortmund, Germany

    Günter Rudolph

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© 2010 Springer-Verlag Berlin Heidelberg

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Tavares, J., Pereira, F.B. (2010). Evolving Strategies for Updating Pheromone Trails: A Case Study with the TSP. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds) Parallel Problem Solving from Nature, PPSN XI. PPSN 2010. Lecture Notes in Computer Science, vol 6239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15871-1_53

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  • DOI: https://doi.org/10.1007/978-3-642-15871-1_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15870-4

  • Online ISBN: 978-3-642-15871-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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