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

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Tavares:2010:PPSN,

• author = "Jorge Tavares and Francisco Baptista Pereira",
• title = "Evolving Strategies for Updating Pheromone Trails: A Case Study with the TSP",
• booktitle = "PPSN 2010 11th International Conference on Parallel Problem Solving From Nature",
• year = "2010",
• editor = "Robert Schaefer and Carlos Cotta and Joanna Kolodziej and Guenter Rudolph",
• publisher = "Springer",
• pages = "523--532",
• series = "Lecture Notes in Computer Science",
• address = "Krakow, Poland",
• month = "11-15 " # sep,
• volume = "6238",
• keywords = "genetic algorithms, genetic programming, genetic programming, ant colony optimisation",
• isbn13 = "978-3-642-15870-4",
• DOI = "doi:10.1007/978-3-642-15871-1_53",
• abstract = "Ant Colony Optimization is a bio-inspired technique that can be applied to solve hard optimisation 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 generalisation capability when applied to larger instances.",
• affiliation = "CISUC, Department of Informatics Engineering, University of Coimbra, Polo II - Pinhal de Marrocos, 3030 Coimbra, Portugal",

}

Genetic Programming entries for Jorge Tavares Francisco Jose Baptista Pereira

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