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Integrating commercial and residential pickup and delivery networks: A case study

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  • Bard, Jonathan F.
  • Jarrah, Ahmad I.
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    Abstract

    This paper presents a strategic analysis of the network design problem faced by pickup and delivery companies operating in metropolitan areas and serving two or more classes of customers. The focus is on a division that treats commercial and residential customers separately, a situation motivated by their respective geographic densities and the size and frequency of their demand. In constructing driver work areas, it is necessary to take into account expected demand, vehicle capacity, time on the road, and the aspect ratio of the individual territories. This leads to a capacitated clustering problem with side constraints that has been the subject of intense research over the last decade.

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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 41 (2013)
    Issue (Month): 4 ()
    Pages: 706-720

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    Handle: RePEc:eee:jomega:v:41:y:2013:i:4:p:706-720

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    Related research

    Keywords: Network design; Pickup and delivery; Case study; Policy analysis; Column generation;

    References

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    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    1. Bard, Jonathan F. & Jarrah, Ahmad I., 2009. "Large-scale constrained clustering for rationalizing pickup and delivery operations," Transportation Research Part B: Methodological, Elsevier, vol. 43(5), pages 542-561, June.
    2. Langevin, André & Soumis, François, 1989. "Design of multiple-vehicle delivery tours satisfying time constraints," Transportation Research Part B: Methodological, Elsevier, vol. 23(2), pages 123-138, April.
    3. Andreas Drexl & Knut Haase, 1999. "Fast Approximation Methods for Sales Force Deployment," Management Science, INFORMS, vol. 45(10), pages 1307-1323, October.
    4. A I Jarrah & J F Bard, 2011. "Pickup and delivery network segmentation using contiguous geographic clustering," Journal of the Operational Research Society, Palgrave Macmillan, vol. 62(10), pages 1827-1843, October.
    5. Bard, Jonathan F. & Jarrah, Ahmad I. & Zan, Jing, 2010. "Validating vehicle routing zone construction using Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 206(1), pages 73-85, October.
    6. Mulvey, John M. & Beck, Michael P., 1984. "Solving capacitated clustering problems," European Journal of Operational Research, Elsevier, vol. 18(3), pages 339-348, December.
    7. Anuj Mehrotra & Ellis L. Johnson & George L. Nemhauser, 1998. "An Optimization Based Heuristic for Political Districting," Management Science, INFORMS, vol. 44(8), pages 1100-1114, August.
    8. Ouyang, Yanfeng, 2007. "Design of vehicle routing zones for large-scale distribution systems," Transportation Research Part B: Methodological, Elsevier, vol. 41(10), pages 1079-1093, December.
    9. Laporte, Gilbert & Chapleau, Suzanne & Landry, Philippe-Eric & Mercure, Hélène, 1989. "An algorithm for the design of mailbox collection routes in urban areas," Transportation Research Part B: Methodological, Elsevier, vol. 23(4), pages 271-280, August.
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    Cited by:
    1. Liu, Ran & Xie, Xiaolan & Garaix, Thierry, 2014. "Hybridization of tabu search with feasible and infeasible local searches for periodic home health care logistics," Omega, Elsevier, vol. 47(C), pages 17-32.

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