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An Effective Memetic Algorithm with Population Management for the Split Delivery Vehicle Routing Problem

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Hybrid Metaheuristics (HM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4771))

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Abstract

This paper studies the Split Delivery Vehicle Routing problem (SDVRP), a variant of the VRP in which multiple visits to customers are allowed. This NP-hard problem is solved by a recent metaheuristic called Memetic Algorithm with Population Management or MA|PM (Sörensen, 2003). It consists in a genetic algorithm, combined with a local search procedure for intensification and a distance measure to control population diversity. Special moves dedicated to split deliveries are introduced in the local search. This solution approach is evaluated and compared with the tabu search algorithm of Archetti et al. (2006) and with lower bounds designed by Belenguer et al. (2000). Our method outperforms the tabu search both in solution quality and running time. On a set of 49 instances, it improves the best-known solution 32 times. The savings obtained confirm the interest and the power of the MA|PM.

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Authors and Affiliations

  1. ICD - OSI, University of Technology of Troyes, 12, Rue Marie Curie, BP 2060, 10010 Troyes, France

    Mourad Boudia, Christian Prins & Mohamed Reghioui

Authors
  1. Mourad Boudia
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  2. Christian Prins
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  3. Mohamed Reghioui
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Editor information

Thomas Bartz-Beielstein María José Blesa Aguilera Christian Blum Boris Naujoks Andrea Roli Günter Rudolph Michael Sampels

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© 2007 Springer-Verlag Berlin Heidelberg

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Boudia, M., Prins, C., Reghioui, M. (2007). An Effective Memetic Algorithm with Population Management for the Split Delivery Vehicle Routing Problem. In: Bartz-Beielstein, T., et al. Hybrid Metaheuristics. HM 2007. Lecture Notes in Computer Science, vol 4771. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75514-2_2

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  • DOI: https://doi.org/10.1007/978-3-540-75514-2_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75513-5

  • Online ISBN: 978-3-540-75514-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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