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Pickup and delivery systems for overnight carriers

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  • Hall, Randolph W.

Abstract

This paper demonstrates how the constraints of overnight delivery affect the design of pickup and delivery systems. Cost depends on the number of vehicle routes needed to pick up and deliver shipments. This number in turn depends on the critical parts of the driver's day: the morning delivery period, up to the delivery deadline; and the afternoon pickup period, after the cutoff time. Pickup routing is the more complicated, due to the dynamic nature of customer calls. Models are developed to assess the workload remaining to be completed at the cutoff time and, from this value, the number of routes required to pick up the shipments.

Suggested Citation

  • Hall, Randolph W., 1996. "Pickup and delivery systems for overnight carriers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(3), pages 173-187, May.
    • Handle: RePEc:eee:transa:v:30:y:1996:i:3:p:173-187
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    References listed on IDEAS

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    1. Hall, Randolph W., 1991. "Design for local Area Freight Networks," University of California Transportation Center, Working Papers qt97v2p2vk, University of California Transportation Center.
    2. David M. Stein, 1978. "Scheduling Dial-a-Ride Transportation Systems," Transportation Science, INFORMS, vol. 12(3), pages 232-249, August.
    3. Morton E. O'Kelly, 1986. "The Location of Interacting Hub Facilities," Transportation Science, INFORMS, vol. 20(2), pages 92-106, May.
    4. David M. Stein, 1978. "An Asymptotic, Probabilistic Analysis of a Routing Problem," Mathematics of Operations Research, INFORMS, vol. 3(2), pages 89-101, May.
    5. Patrick Jaillet, 1988. "A Priori Solution of a Traveling Salesman Problem in Which a Random Subset of the Customers Are Visited," Operations Research, INFORMS, vol. 36(6), pages 929-936, December.
    6. Hall, Randolph W., 1991. "Design for Local Area Freight Networks," University of California Transportation Center, Working Papers qt72s9d408, University of California Transportation Center.
    7. Carlos F. Daganzo, 1984. "The Distance Traveled to Visit N Points with a Maximum of C Stops per Vehicle: An Analytic Model and an Application," Transportation Science, INFORMS, vol. 18(4), pages 331-350, November.
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    Cited by:

    1. 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.
    2. Diana, Marco & Dessouky, Maged M. & Xia, Nan, 2006. "A model for the fleet sizing of demand responsive transportation services with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 40(8), pages 651-666, September.
    3. Beatrice Marchi & Simone Zanoni & Mohamad Y. Jaber, 2020. "Energy Implications of Lot Sizing Decisions in Refrigerated Warehouses," Energies, MDPI, vol. 13(7), pages 1-13, April.
    4. Hande Yaman & Oya Ekin Karasan & Bahar Y. Kara, 2012. "Release Time Scheduling and Hub Location for Next-Day Delivery," Operations Research, INFORMS, vol. 60(4), pages 906-917, August.
    5. Hongsheng Zhong & Randolph W. Hall & Maged Dessouky, 2007. "Territory Planning and Vehicle Dispatching with Driver Learning," Transportation Science, INFORMS, vol. 41(1), pages 74-89, February.

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