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An exact solution approach for vehicle routing and scheduling problems with soft time windows

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Author Info

  • Qureshi, A.G.
  • Taniguchi, E.
  • Yamada, T.
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    Abstract

    A new column generation based exact optimization approach for the vehicle routing and scheduling problem with semi soft time windows (VRPSSTW) is presented. Elementary shortest path problem with resource constraints and late arrival penalties is solved as a subproblem, which rises from the Dantzig-Wolfe decomposition method. Exact solutions of VRPSSTW and hard time windows variant are compared on Solomon's benchmark instances as well as on an instance based on Tokyo road network. It was found that the VRPSSTW solution results in fewer routes thus overall costs are reduced and late arrival penalties contribute only a small fraction to total cost.

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    File URL: http://www.sciencedirect.com/science/article/pii/S1366554509000428
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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part E: Logistics and Transportation Review.

    Volume (Year): 45 (2009)
    Issue (Month): 6 (November)
    Pages: 960-977

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    Handle: RePEc:eee:transe:v:45:y:2009:i:6:p:960-977

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    Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description

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    Related research

    Keywords: City logistics Vehicle routing with soft time windows Column generation;

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    Cited by:
    1. Lau, Kwok Hung, 2013. "Measuring distribution efficiency of a retail network through data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 146(2), pages 598-611.
    2. Bhusiri, Narath & Qureshi, Ali Gul & Taniguchi, Eiichi, 2014. "The trade-off between fixed vehicle costs and time-dependent arrival penalties in a routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 1-22.
    3. N. Norouzi & R. Tavakkoli-Moghaddam & M. Ghazanfari & M. Alinaghian & A. Salamatbakhsh, 2012. "A New Multi-objective Competitive Open Vehicle Routing Problem Solved by Particle Swarm Optimization," Networks and Spatial Economics, Springer, vol. 12(4), pages 609-633, December.

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