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Ant Metaheuristic with Adapted Personalities for the Vehicle Routing Problem

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Computational Logistics (ICCL 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9335))

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Abstract

At each generation of an ant algorithm, each ant builds a solution step by step by adding an element to it. Each choice is based on the greedy force (short term profit or heuristic information) and the trail system (central memory which collects information during the search process). Usually, all the ants of the population have the same characteristics and behaviors. In contrast in this paper, a new type of ant metaheuristic is proposed. It relies on the use of ants with different personalities. Such a method has been adapted to the well-known vehicle routing problem, and even if it does not match the best known results, its performance is encouraging (on one benchmark instance, new best results have however been found), which opens the door to a new ant algorithm paradigm.

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Author information

Authors and Affiliations

  1. Geneva School of Economics and Management, GSEM - University of Geneva, Blvd du Pont-d’Arve 40, 1211, Geneva 4, Switzerland

    Nicolas Zufferey

  2. ETSEIB, Universitat Politècnica de Catalunya, Barcelona, Spain

    Jaime Farres

  3. LGPP, École Polytechnique Fédérale Lausanne, Lausanne, Switzerland

    Rémy Glardon

Authors
  1. Nicolas Zufferey
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  2. Jaime Farres
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  3. Rémy Glardon
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Corresponding author

Correspondence to Jaime Farres .

Editor information

Editors and Affiliations

  1. Delft University of Technology, Delft, The Netherlands

    Francesco Corman

  2. University of Hamburg, Hamburg, Germany

    Stefan Voß

  3. Delft University of Technology, Delft, The Netherlands

    Rudy R. Negenborn

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Zufferey, N., Farres, J., Glardon, R. (2015). Ant Metaheuristic with Adapted Personalities for the Vehicle Routing Problem. In: Corman, F., Voß, S., Negenborn, R. (eds) Computational Logistics. ICCL 2015. Lecture Notes in Computer Science(), vol 9335. Springer, Cham. https://doi.org/10.1007/978-3-319-24264-4_1

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  • DOI: https://doi.org/10.1007/978-3-319-24264-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24263-7

  • Online ISBN: 978-3-319-24264-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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