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Self-organization and Evolution Combined to Address the Vehicle Routing Problem

  • Conference paper
Artificial Evolution (EA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4926))

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Abstract

The paper deals with a self-organizing system in a evolutionary framework applied to the Euclidean Vehicle Routing Problem (VRP). Theoretically, self-organization is intended to allow adaptation to noisy data as well as to confer robustness according to demand fluctuation. Evolution through selection is intended to guide a population based search toward near-optimal solutions. To implement such principles to address the VRP, the approach uses the standard self-organizing map algorithm as a main operator embedded in a evolutionary loop. We evaluate the approach on standard benchmark problems and show that it performs better, with respect to solution quality and/or computation time, than other self-organizing neural networks to the VRP presented in the literature. As well, it substantially reduces the gap to some classical Operations Research heuristics.

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Authors and Affiliations

  1. Systems and Transportation Laboratory, University of Technology of Belfort-Montbeliard, 90010, Belfort, France

    Jean-Charles Créput & Abderrafiaâ Koukam

Authors
  1. Jean-Charles Créput
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  2. Abderrafiaâ Koukam
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Editor information

Nicolas Monmarché El-Ghazali Talbi Pierre Collet Marc Schoenauer Evelyne Lutton

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Créput, JC., Koukam, A. (2008). Self-organization and Evolution Combined to Address the Vehicle Routing Problem. In: Monmarché, N., Talbi, EG., Collet, P., Schoenauer, M., Lutton, E. (eds) Artificial Evolution. EA 2007. Lecture Notes in Computer Science, vol 4926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79305-2_9

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  • DOI: https://doi.org/10.1007/978-3-540-79305-2_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79304-5

  • Online ISBN: 978-3-540-79305-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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