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Quantifying the value of advance load information in truckload trucking

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  • Tjokroamidjojo, Darsono
  • Kutanoglu, Erhan
  • Taylor, G. Don

Abstract

We present an optimization-based computational study to quantify the relative benefits and costs of sharing advance load information and preparing an advance pick-up and delivery plan (or preplanning) in load assignment problems in truckload trucking. Considering that the benefits of preplanning comes in many intangible forms, we take the strategy of showing the cost differences between preplanning and different forms of dispatching, instead of computing the benefits directly. Computational study under several settings not only shows the benefit of using advanced load information, but also uncovers the minimal cost difference between intelligent preplanning and the best performing dispatching policies.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:transe:v:42:y:2006:i:4:p:340-357
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    Citations

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    Cited by:

    1. Xue, Zhaojie & Zhang, Canrong & Lin, Wei-Hua & Miao, Lixin & Yang, Peng, 2014. "A tabu search heuristic for the local container drayage problem under a new operation mode," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 136-150.
    2. Zolfagharinia, Hossein & Haughton, Michael, 2014. "The benefit of advance load information for truckload carriers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 34-54.
    3. Zolfagharinia, Hossein & Haughton, Michael, 2016. "Effective truckload dispatch decision methods with incomplete advance load information," European Journal of Operational Research, Elsevier, vol. 252(1), pages 103-121.
    4. Berbeglia, Gerardo & Cordeau, Jean-François & Laporte, Gilbert, 2010. "Dynamic pickup and delivery problems," European Journal of Operational Research, Elsevier, vol. 202(1), pages 8-15, April.
    5. Florian Dandl & Michael Hyland & Klaus Bogenberger & Hani S. Mahmassani, 2019. "Evaluating the impact of spatio-temporal demand forecast aggregation on the operational performance of shared autonomous mobility fleets," Transportation, Springer, vol. 46(6), pages 1975-1996, December.
    6. Zhang, Hongtao & Lee, Chung-Yee & Li, Tian, 2016. "The value of specific cargo information for substitutable modes of inland transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 85(C), pages 23-39.
    7. Acocella, Angela & Caplice, Chris & Sheffi, Yossi, 2020. "Elephants or goldfish?: An empirical analysis of carrier reciprocity in dynamic freight markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    8. Stefan Vonolfen & Michael Affenzeller, 2016. "Distribution of waiting time for dynamic pickup and delivery problems," Annals of Operations Research, Springer, vol. 236(2), pages 359-382, January.
    9. Hamed Faroqi & Abolghasem Sadeghi-Niaraki, 2016. "GIS-based ride-sharing and DRT in Tehran city," Public Transport, Springer, vol. 8(2), pages 243-260, September.
    10. Scott, Alex, 2015. "The value of information sharing for truckload shippers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 203-214.
    11. Budak, Aysenur & Ustundag, Alp & Guloglu, Bulent, 2017. "A forecasting approach for truckload spot market pricing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 55-68.
    12. Rob A. Zuidwijk & Albert W. Veenstra, 2015. "The Value of Information in Container Transport," Transportation Science, INFORMS, vol. 49(3), pages 675-685, August.
    13. Woxenius, Johan, 2007. "Alternative transport network designs and their implications for intermodal transhipment technologies," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 35, pages 27-45.
    14. Srour, F.J. & Agatz, N.A.H. & Oppen, J., 2014. "The Value of Inaccurate Advance Time Window Information in a Pick-up and Delivery Problem," ERIM Report Series Research in Management ERS-2014-002-LIS, 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.
    15. Viet, Nguyen Quoc & Behdani, Behzad & Bloemhof, Jacqueline, 2018. "Value of Information to Improve Daily Operations in High-Density Logistics," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 9(1), January.
    16. Zolfagharinia, Hossein & Haughton, Michael A., 2017. "Operational flexibility in the truckload trucking industry," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 437-460.
    17. Zolfagharinia, Hossein & Haughton, Michael, 2018. "The importance of considering non-linear layover and delay costs for local truckers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 331-355.
    18. Stefan Vonolfen & Michael Affenzeller, 2016. "Distribution of waiting time for dynamic pickup and delivery problems," Annals of Operations Research, Springer, vol. 236(2), pages 359-382, January.

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