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The Value of Inaccurate Advance Time Window Information in a Pick-up and Delivery Problem

Listed author(s):
  • Srour, F.J.
  • Agatz, N.A.H.
  • Oppen, J.
Registered author(s):

    We examine different routing strategies to cope with inaccurate time window in- formation in the context of a dynamic pick-up and delivery problem with time windows. Our experiments show that advance information, even if inaccurate, can provide benefits from a planning perspective. We propose a novel stochastic strategy that consistently performs well compared to several benchmark strategies.

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    Paper provided by Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam in its series ERIM Report Series Research in Management with number ERS-2014-002-LIS.

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    Date of creation: 27 Jan 2014
    Handle: RePEc:ems:eureri:50394
    Contact details of provider: Postal:
    RSM Erasmus University & Erasmus School of Economics, PoBox 1738, 3000 DR Rotterdam

    Phone: 31-10-408 1182
    Fax: 31-10-408 9020
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    1. Tjokroamidjojo, Darsono & Kutanoglu, Erhan & Taylor, G. Don, 2006. "Quantifying the value of advance load information in truckload trucking," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(4), pages 340-357, July.
    2. Soumia Ichoua & Michel Gendreau & Jean-Yves Potvin, 2006. "Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching," Transportation Science, INFORMS, vol. 40(2), pages 211-225, May.
    3. Barrett W. Thomas & Chelsea C. White, 2004. "Anticipatory Route Selection," Transportation Science, INFORMS, vol. 38(4), pages 473-487, November.
    4. Mitrovic-Minic, Snezana & Krishnamurti, Ramesh & Laporte, Gilbert, 2004. "Double-horizon based heuristics for the dynamic pickup and delivery problem with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 38(8), pages 669-685, September.
    5. Gianpaolo Ghiani & Emanuele Manni & Barrett W. Thomas, 2012. "A Comparison of Anticipatory Algorithms for the Dynamic and Stochastic Traveling Salesman Problem," Transportation Science, INFORMS, vol. 46(3), pages 374-387, August.
    6. Ghiani, Gianpaolo & Guerriero, Francesca & Laporte, Gilbert & Musmanno, Roberto, 2003. "Real-time vehicle routing: Solution concepts, algorithms and parallel computing strategies," European Journal of Operational Research, Elsevier, vol. 151(1), pages 1-11, November.
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