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Multi-hop driver-parcel matching problem with time windows

Author

Listed:
  • Wenyi Chen

    (University of Twente
    ESC Rennes School of Business)

  • Martijn Mes

    (University of Twente)

  • Marco Schutten

    (University of Twente)

Abstract

Crowdsourced shipping can result in significant economic and social benefits. For a shipping company, it has a potential cost advantage and creates opportunities for faster deliveries. For the society, it can provide desirable results by reducing congestion and air pollution. Despite the great potential, crowdsourced shipping is not well studied. With the aim of using the spare capacities along the existing transportation flows of the crowd to deliver small-to-medium freight volumes, this paper defines the multi-driver multi-parcel matching problem and proposes a general ILP formulation, which incorporates drivers’ maximum detour, capacity limits, and the option of transferring parcels between drivers. Due to the high computational complexity, we develop two heuristics to solve the problem. The numerical study shows that crowdsourced shipping can be an economic viable and sustainable option, depending on the spatial characteristics of the network and drivers’ schedules. Furthermore, the added benefits increase with an increasing number of participating drivers and parcels.

Suggested Citation

  • Wenyi Chen & Martijn Mes & Marco Schutten, 2018. "Multi-hop driver-parcel matching problem with time windows," Flexible Services and Manufacturing Journal, Springer, vol. 30(3), pages 517-553, September.
    • Handle: RePEc:spr:flsman:v:30:y:2018:i:3:d:10.1007_s10696-016-9273-3
    DOI: 10.1007/s10696-016-9273-3
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    References listed on IDEAS

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    Cited by:

    1. Nils Boysen & Stefan Fedtke & Stefan Schwerdfeger, 2021. "Last-mile delivery concepts: a survey from an operational research perspective," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 1-58, March.
    2. Fessler, Andreas & Cash, Philip & Thorhauge, Mikkel & Haustein, Sonja, 2023. "A public transport based crowdshipping concept: Results of a field test in Denmark," Transport Policy, Elsevier, vol. 134(C), pages 106-118.
    3. Zehtabian, Shohre & Larsen, Christian & Wøhlk, Sanne, 2022. "Estimation of the arrival time of deliveries by occasional drivers in a crowd-shipping setting," European Journal of Operational Research, Elsevier, vol. 303(2), pages 616-632.
    4. Kong, Xiang T.R. & Kang, Kai & Zhong, Ray Y. & Luo, Hao & Xu, Su Xiu, 2021. "Cyber physical system-enabled on-demand logistics trading," International Journal of Production Economics, Elsevier, vol. 233(C).
    5. Yıldız, Barış, 2021. "Package routing problem with registered couriers and stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    6. Shen, Hui & Lin, Jane, 2020. "Investigation of crowdshipping delivery trip production with real-world data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    7. Allahviranloo, Mahdieh & Baghestani, Amirhossein, 2019. "A dynamic crowdshipping model and daily travel behavior," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 175-190.
    8. Behrend, Moritz & Meisel, Frank & Fagerholt, Kjetil & Andersson, Henrik, 2021. "A multi-period analysis of the integrated item-sharing and crowdshipping problem," European Journal of Operational Research, Elsevier, vol. 292(2), pages 483-499.
    9. Azcuy, Irecis & Agatz, Niels & Giesen, Ricardo, 2021. "Designing integrated urban delivery systems using public transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    10. Mario Binetti & Leonardo Caggiani & Rosalia Camporeale & Michele Ottomanelli, 2019. "A Sustainable Crowdsourced Delivery System to Foster Free-Floating Bike-Sharing," Sustainability, MDPI, vol. 11(10), pages 1-24, May.
    11. Heru Susanto & Nurul Kemaluddin, 2023. "Innovative Blockchain-Based Tracking Systems, A Technology Acceptance for Cross-Border Runners during and Post-Pandemic," Sustainability, MDPI, vol. 15(8), pages 1-34, April.
    12. Wang, Li & Xu, Min & Qin, Hu, 2023. "Joint optimization of parcel allocation and crowd routing for crowdsourced last-mile delivery," Transportation Research Part B: Methodological, Elsevier, vol. 171(C), pages 111-135.
    13. Behrend, Moritz & Meisel, Frank & Fagerholt, Kjetil & Andersson, Henrik, 2019. "An exact solution method for the capacitated item-sharing and crowdshipping problem," European Journal of Operational Research, Elsevier, vol. 279(2), pages 589-604.

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