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International Conference on Computational Logistics

ICCL 2017: Computational Logistics pp 143–157Cite as

Metaheuristic Framework for a Disaster Logistics Problem with Time-Dependent Demands

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10572))

Abstract

This paper addresses a novel capacitated vehicle routing problem with time-dependent demands (CVRP-TDD) arising in a relief distribution situation in a region struck by the disaster. The locations closest to the epicenter are the ones hit hardest and the natural reaction of survivors is to flee from these points, called critical nodes. Lacks or delays in relief distribution amplify this behavior. To reduce this phenomenon, we aim to maximize the demand satisfied at the critical nodes. We present an optimal splitting procedure and a metaheuristic framework that can execute four different methods, by changing only three parameters. The results shows the good performance of two methods and highlight the efficiency of the splitting procedure.

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Author information

Authors and Affiliations

  1. ICD-LOSI, Université de Technologie de Troyes, UMR CNRS 6281, 12 Rue Marie Curie, CS 42060, 10004, Troyes Cedex, France

    Jorge F. Victoria, H. Murat Afsar & Christian Prins

Authors
  1. Jorge F. Victoria
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  2. H. Murat Afsar
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  3. Christian Prins
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Corresponding author

Correspondence to Jorge F. Victoria .

Editor information

Editors and Affiliations

  1. University of Southampton , Southampton, United Kingdom

    Tolga Bektaş

  2. University of Southampton , Southampton, United Kingdom

    Stefano Coniglio

  3. University of Southampton , Southampton, United Kingdom

    Antonio Martinez-Sykora

  4. University of Hamburg , Hamburg, Germany

    Stefan Voß

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Victoria, J.F., Afsar, H.M., Prins, C. (2017). Metaheuristic Framework for a Disaster Logistics Problem with Time-Dependent Demands. In: Bektaş, T., Coniglio, S., Martinez-Sykora, A., Voß, S. (eds) Computational Logistics. ICCL 2017. Lecture Notes in Computer Science(), vol 10572. Springer, Cham. https://doi.org/10.1007/978-3-319-68496-3_10

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  • DOI: https://doi.org/10.1007/978-3-319-68496-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68495-6

  • Online ISBN: 978-3-319-68496-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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