IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v165y2022ics1366554522002253.html
   My bibliography  Save this article

Community logistics for dynamic vehicle dispatching: The effects of community departure “time” and “space”

Author

Listed:
  • Ouyang, Zhiyuan
  • Leung, Eric Ka Ho
  • Huang, George Q.

Abstract

The rise of e-commerce has completely transformed the dynamicity and problem nature of last-mile delivery, owing to significant B2C customer demand in compact urban areas. Given the unprecedented growths of urban last-mile deliveries, this paper proposes a novel postponement prioritized-route optional approach, namely Community Logistics (CL), as a new logistics tool to manage dynamic arrivals of delivery requests received in e-commerce hubs. Each vehicle is responsible for serving a “community”. At each decision epoch, fragmented e-commerce delivery requests arrived at the depot are either allocated to a community or postponed to later epochs for actual last-mile delivery. With an objective of consolidating newly arrived requests, we develop two dynamic policies – temporal and spatial, respectively for temporally delaying vehicle’s departure and spatially allocating more pre-partitioned geographical cells into one community. The main contribution of this study lies in a spatiotemporal relativity analysis and a comparative analysis. The former demonstrates the essence of incorporating both dynamic community departure times and dynamic community regions into managing urban e-commerce deliveries, whereas the latter validates the merits of Community Logistics against dynamic vehicle routing solutions. In the end, we call for further developments of community logistics strategies to address the impacts of urban deliveries due to the rise of e-commerce and online shopping.

Suggested Citation

  • Ouyang, Zhiyuan & Leung, Eric Ka Ho & Huang, George Q., 2022. "Community logistics for dynamic vehicle dispatching: The effects of community departure “time” and “space”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
  • Handle: RePEc:eee:transe:v:165:y:2022:i:c:s1366554522002253
    DOI: 10.1016/j.tre.2022.102842
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554522002253
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tre.2022.102842?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Briseida Sarasola & Karl Doerner & Verena Schmid & Enrique Alba, 2016. "Variable neighborhood search for the stochastic and dynamic vehicle routing problem," Annals of Operations Research, Springer, vol. 236(2), pages 425-461, January.
    2. A Poot & G Kant & A P M Wagelmans, 2002. "A savings based method for real-life vehicle routing problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(1), pages 57-68, January.
    3. Stacy A. Voccia & Ann Melissa Campbell & Barrett W. Thomas, 2019. "The Same-Day Delivery Problem for Online Purchases," Service Science, INFORMS, vol. 53(1), pages 167-184, February.
    4. Alan S. Minkoff, 1993. "A Markov Decision Model and Decomposition Heuristic for Dynamic Vehicle Dispatching," Operations Research, INFORMS, vol. 41(1), pages 77-90, February.
    5. John Gunnar Carlsson, 2012. "Dividing a Territory Among Several Vehicles," INFORMS Journal on Computing, INFORMS, vol. 24(4), pages 565-577, November.
    6. Laporte, Gilbert, 1992. "The traveling salesman problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(2), pages 231-247, June.
    7. Mitrovic-Minic, Snezana & Laporte, Gilbert, 2004. "Waiting strategies for the dynamic pickup and delivery problem with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 38(7), pages 635-655, August.
    8. Guodong Yu & Yu Yang, 2019. "Dynamic routing with real-time traffic information," Operational Research, Springer, vol. 19(4), pages 1033-1058, December.
    9. John Gunnar Carlsson & Erick Delage, 2013. "Robust Partitioning for Stochastic Multivehicle Routing," Operations Research, INFORMS, vol. 61(3), pages 727-744, June.
    10. Martin Savelsbergh & Tom Van Woensel, 2016. "50th Anniversary Invited Article—City Logistics: Challenges and Opportunities," Transportation Science, INFORMS, vol. 50(2), pages 579-590, May.
    11. Huang, Yixiao & Savelsbergh, Martin & Zhao, Lei, 2018. "Designing logistics systems for home delivery in densely populated urban areas," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 95-125.
    12. Briseida Sarasola & Karl F. Doerner & Verena Schmid & Enrique Alba, 2016. "Variable neighborhood search for the stochastic and dynamic vehicle routing problem," Annals of Operations Research, Springer, vol. 236(2), pages 425-461, January.
    13. Hintsch, Timo & Irnich, Stefan, 2018. "Large multiple neighborhood search for the clustered vehicle-routing problem," European Journal of Operational Research, Elsevier, vol. 270(1), pages 118-131.
    14. Zhou, Lin & Zhen, Lu & Baldacci, Roberto & Boschetti, Marco & Dai, Ying & Lim, Andrew, 2021. "A Heuristic Algorithm for solving a large-scale real-world territory design problem," Omega, Elsevier, vol. 103(C).
    15. Marlin W. Ulmer & Dirk C. Mattfeld & Felix Köster, 2018. "Budgeting Time for Dynamic Vehicle Routing with Stochastic Customer Requests," Transportation Science, INFORMS, vol. 52(1), pages 20-37, January.
    16. Matthias Winkenbach & Paul R. Kleindorfer & Stefan Spinler, 2016. "Enabling Urban Logistics Services at La Poste through Multi-Echelon Location-Routing," Transportation Science, INFORMS, vol. 50(2), pages 520-540, May.
    17. Mourão, Maria Cândida & Nunes, Ana Catarina & Prins, Christian, 2009. "Heuristic methods for the sectoring arc routing problem," European Journal of Operational Research, Elsevier, vol. 196(3), pages 856-868, August.
    18. Bender, Matthias & Kalcsics, Jörg & Meyer, Anne, 2020. "Districting for parcel delivery services – A two-Stage solution approach and a real-World case study," Omega, Elsevier, vol. 96(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang, Yitao & Jia, Bin & Yan, Xiao-Yong & Zhi, Danyue & Song, Dongdong & Chen, Yan & de Bok, Michiel & Tavasszy, Lóránt A. & Gao, Ziyou, 2023. "Uncovering and modeling the hierarchical organization of urban heavy truck flows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ouyang, Zhiyuan & Leung, Eric K.H. & Huang, George Q., 2023. "Community logistics and dynamic community partitioning: A new approach for solving e-commerce last mile delivery," European Journal of Operational Research, Elsevier, vol. 307(1), pages 140-156.
    2. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
    3. Ritzinger, Ulrike & Puchinger, Jakob & Rudloff, Christian & Hartl, Richard F., 2022. "Comparison of anticipatory algorithms for a dial-a-ride problem," European Journal of Operational Research, Elsevier, vol. 301(2), pages 591-608.
    4. Zhen, Lu & Gao, Jiajing & Tan, Zheyi & Laporte, Gilbert & Baldacci, Roberto, 2023. "Territorial design for customers with demand frequency," European Journal of Operational Research, Elsevier, vol. 309(1), pages 82-101.
    5. 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.
    6. Soeffker, Ninja & Ulmer, Marlin W. & Mattfeld, Dirk C., 2022. "Stochastic dynamic vehicle routing in the light of prescriptive analytics: A review," European Journal of Operational Research, Elsevier, vol. 298(3), pages 801-820.
    7. Marlin W. Ulmer, 2020. "Horizontal combinations of online and offline approximate dynamic programming for stochastic dynamic vehicle routing," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 279-308, March.
    8. Koch, Sebastian & Klein, Robert, 2020. "Route-based approximate dynamic programming for dynamic pricing in attended home delivery," European Journal of Operational Research, Elsevier, vol. 287(2), pages 633-652.
    9. Snoeck, André & Winkenbach, Matthias & Fransoo, Jan C., 2023. "On-demand last-mile distribution network design with omnichannel inventory," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    10. Snoeck, André & Winkenbach, Matthias & Fransoo, Jan C., 2023. "On-demand last-mile distribution network design with omnichannel inventory," Other publications TiSEM 83b06c9f-2a65-4aaf-880b-2, Tilburg University, School of Economics and Management.
    11. Vidal, Thibaut & Laporte, Gilbert & Matl, Piotr, 2020. "A concise guide to existing and emerging vehicle routing problem variants," European Journal of Operational Research, Elsevier, vol. 286(2), pages 401-416.
    12. Côté, Jean-François & Alves de Queiroz, Thiago & Gallesi, Francesco & Iori, Manuel, 2023. "A branch-and-regret algorithm for the same-day delivery problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    13. Diglio, Antonio & Peiró, Juanjo & Piccolo, Carmela & Saldanha-da-Gama, Francisco, 2023. "Approximation schemes for districting problems with probabilistic constraints," European Journal of Operational Research, Elsevier, vol. 307(1), pages 233-248.
    14. Haider, Zulqarnain & Hu, Yujie & Charkhgard, Hadi & Himmelgreen, David & Kwon, Changhyun, 2022. "Creating grocery delivery hubs for food deserts at local convenience stores via spatial and temporal consolidation," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    15. Olivera Janković & Stefan Mišković & Zorica Stanimirović & Raca Todosijević, 2017. "Novel formulations and VNS-based heuristics for single and multiple allocation p-hub maximal covering problems," Annals of Operations Research, Springer, vol. 259(1), pages 191-216, December.
    16. Fleckenstein, David & Klein, Robert & Steinhardt, Claudius, 2023. "Recent advances in integrating demand management and vehicle routing: A methodological review," European Journal of Operational Research, Elsevier, vol. 306(2), pages 499-518.
    17. Sluijk, Natasja & Florio, Alexandre M. & Kinable, Joris & Dellaert, Nico & Van Woensel, Tom, 2023. "Two-echelon vehicle routing problems: A literature review," European Journal of Operational Research, Elsevier, vol. 304(3), pages 865-886.
    18. Masmoudi, Mohamed Amine & Hosny, Manar & Demir, Emrah & Genikomsakis, Konstantinos N. & Cheikhrouhou, Naoufel, 2018. "The dial-a-ride problem with electric vehicles and battery swapping stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 392-420.
    19. Ulmer, Marlin W. & Soeffker, Ninja & Mattfeld, Dirk C., 2018. "Value function approximation for dynamic multi-period vehicle routing," European Journal of Operational Research, Elsevier, vol. 269(3), pages 883-899.
    20. Marlin Ulmer & Martin Savelsbergh, 2020. "Workforce Scheduling in the Era of Crowdsourced Delivery," Transportation Science, INFORMS, vol. 54(4), pages 1113-1133, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:165:y:2022:i:c:s1366554522002253. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.