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A Simulated Annealing Algorithm for the Vehicle Routing Problem with Time Windows and Synchronization Constraints

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Learning and Intelligent Optimization (LION 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7997))

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Abstract

This paper focuses on solving a variant of the vehicle routing problem (VRP) in which a time window is associated with each customer service and some services require simultaneous visits from different vehicles to be accomplished. The problem is therefore called the VRP with time windows and synchronization constraints (VRPTWSyn). We present a simulated annealing algorithm (SA) that incorporates several local search techniques to deal with this problem. Experiments on the instances from the literature show that our SA is fast and outperforms the existing approaches. To the best of our knowledge, this is the first time that dedicated local search methods have been proposed and evaluated on this variant of VRP.

This work is partially supported by the Regional Council of Picardie and the European Regional Development Fund (ERDF), under PRIMA project.

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Author information

Authors and Affiliations

  1. Université de Technologie de Compiègne, Laboratoire Heudiasyc, UMR 7253 CNRS, Compiègne, 60205, France

    Sohaib Afifi, Duc-Cuong Dang & Aziz Moukrim

  2. School of Computer Science, ASAP Research Group, University of Nottingham, Jubilee Campus, Wollaton Road, Nottingham, NG8 1BB, UK

    Duc-Cuong Dang

Authors
  1. Sohaib Afifi
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  2. Duc-Cuong Dang
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  3. Aziz Moukrim
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Corresponding author

Correspondence to Sohaib Afifi .

Editor information

Editors and Affiliations

  1. Università Catania Dipto. Matematica e Informatica, Catania, Italy

    Giuseppe Nicosia

  2. Industrial & Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos Pardalos

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Afifi, S., Dang, DC., Moukrim, A. (2013). A Simulated Annealing Algorithm for the Vehicle Routing Problem with Time Windows and Synchronization Constraints. In: Nicosia, G., Pardalos, P. (eds) Learning and Intelligent Optimization. LION 2013. Lecture Notes in Computer Science(), vol 7997. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44973-4_27

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  • DOI: https://doi.org/10.1007/978-3-642-44973-4_27

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-44972-7

  • Online ISBN: 978-3-642-44973-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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