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Integration of the Load-Matching and Routing Problem with Equipment Balancing for Small Package Carriers

Author

Listed:
  • Amy Cohn

    (Industrial and Operations Engineering, University of Michigan, 2797 IOE Building, 1205 Beal Avenue, Ann Arbor, Michigan 48109)

  • Sarah Root

    (Industrial and Operations Engineering, University of Michigan, 2797 IOE Building, 1205 Beal Avenue, Ann Arbor, Michigan 48109)

  • Alex Wang

    (Industrial and Operations Engineering, University of Michigan, 2797 IOE Building, 1205 Beal Avenue, Ann Arbor, Michigan 48109)

  • Douglas Mohr

    (United Parcel Service, 2311 York Road, Timonium, Maryland 21093)

Abstract

Small package delivery is a multibillion dollar industry with complex planning decisions required to efficiently utilize costly resources and meet tight time requirements. The planning process is typically decomposed into sequential subproblems to establish tractability. This decomposition can greatly degrade solution quality. This paper therefore considers the integration of two closely related key subproblems: load matching and routing and equipment balancing . First, we identify critical challenges faced in trying to solve these problems. Then we present a novel modeling approach to address these challenges. Finally, we conclude with computational results from United Parcel Service, the world’s largest package delivery company, demonstrating an improvement of approximately 5% over the company’s existing methods for solving this pair of problems.

Suggested Citation

  • Amy Cohn & Sarah Root & Alex Wang & Douglas Mohr, 2007. "Integration of the Load-Matching and Routing Problem with Equipment Balancing for Small Package Carriers," Transportation Science, INFORMS, vol. 41(2), pages 238-252, May.
    • Handle: RePEc:inm:ortrsc:v:41:y:2007:i:2:p:238-252
    DOI: 10.1287/trsc.1060.0174
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    References listed on IDEAS

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    2. Yan Cheng Hsu & Jose L. Walteros & Rajan Batta, 2020. "Solving the petroleum replenishment and routing problem with variable demands and time windows," Annals of Operations Research, Springer, vol. 294(1), pages 9-46, November.
    3. Giuliano, Genevieve & Showalter, Catherine & Yuan, Quan & Zhang, Rui, 2018. "Managing the Impacts of Freight in California," Institute of Transportation Studies, Working Paper Series qt6614p4js, Institute of Transportation Studies, UC Davis.
    4. Jose L. Andrade-Pineda & Pedro L. Gonzalez-R & Jose M. Framinan, 2013. "A Decision-Making Tool for a Regional Network of Clinical Laboratories," Interfaces, INFORMS, vol. 43(4), pages 360-372, August.
    5. Zhang, Huili & Luo, Kelin & Xu, Yao & Xu, Yinfeng & Tong, Weitian, 2022. "Online crowdsourced truck delivery using historical information," European Journal of Operational Research, Elsevier, vol. 301(2), pages 486-501.
    6. Sarah Root & Amy Cohn, 2008. "A novel modeling approach for express package carrier planning," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 670-683, October.
    7. Le, Tho V. & Ukkusuri, Satish V. & Xue, Jiawei & Van Woensel, Tom, 2021. "Designing pricing and compensation schemes by integrating matching and routing models for crowd-shipping systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    8. Werners, Brigitte & Wülfing, Thomas, 2010. "Robust optimization of internal transports at a parcel sorting center operated by Deutsche Post World Net," European Journal of Operational Research, Elsevier, vol. 201(2), pages 419-426, March.
    9. Ada Y. Barlatt & Amy Cohn & Oleg Gusikhin & Yakov Fradkin & Rich Davidson & John Batey, 2012. "Ford Motor Company Implements Integrated Planning and Scheduling in a Complex Automotive Manufacturing Environment," Interfaces, INFORMS, vol. 42(5), pages 478-491, October.

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