IDEAS home Printed from https://ideas.repec.org/a/spr/comgts/v22y2025i2d10.1007_s10287-025-00545-2.html

Bi-objective green vehicle routing problem with heterogeneous regular vehicles and occasional drivers joint delivery

Author

Listed:
  • Fuqiang Lu

    (Yanshan University)

  • Zhiyuan Gao

    (Yanshan University)

  • Hualing Bi

    (Yanshan University)

Abstract

The paper investigates a bi-objective green vehicle routing problem (GVRP) involving heterogeneous regular vehicles and occasional drivers joint delivery (GVRP-HVOV). This includes soft and hard time windows, earliness, and tardiness penalties. This study proposed for the first time to apply the crowdsourced mode to the road cargo transportation of trucks, and further expanded the scope of use of the crowdsourced mode. Considering the difference between the vehicle’s own attributes and road conditions between truck transportation and the last kilometer delivery, a new crowdsourced mode setting and vehicle path setting were established for truck transportation. A bi-objective programming model is established to minimize total transportation cost as the first objective and reduce total greenhouse gas emissions as the second objective, aiming to strike a balance between transportation cost and carbon emissions, minimizing both. To address this problem, an improved non-dominated sorting genetic algorithm II (NSGA II) is proposed to enhance the quality of the generated population. Additionally, the algorithm’s performance is evaluated using different scale test data to demonstrate its superiority. Finally, instance tests from Walmart show that joint delivery with occasional drivers effectively reduces total costs and greenhouse gas emissions. The study provides useful recommendations for actual logistics companies in planning vehicle types and applying new models. Additionally, sensitivity analysis on the available number of occasional drivers and their delivery range offers a more comprehensive analysis of the impact of joint delivery with occasional drivers on total costs and carbon dioxide emissions in the delivery process.

Suggested Citation

  • Fuqiang Lu & Zhiyuan Gao & Hualing Bi, 2025. "Bi-objective green vehicle routing problem with heterogeneous regular vehicles and occasional drivers joint delivery," Computational Management Science, Springer, vol. 22(2), pages 1-45, December.
  • Handle: RePEc:spr:comgts:v:22:y:2025:i:2:d:10.1007_s10287-025-00545-2
    DOI: 10.1007/s10287-025-00545-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10287-025-00545-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10287-025-00545-2?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Bektas, Tolga & Laporte, Gilbert, 2011. "The Pollution-Routing Problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1232-1250, September.
    2. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2014. "The fleet size and mix pollution-routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 239-254.
    3. Xu, Dongyang & Li, Kunpeng & Zou, Xuxia & Liu, Ling, 2017. "An unpaired pickup and delivery vehicle routing problem with multi-visit," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 218-247.
    4. Erdoğan, Sevgi & Miller-Hooks, Elise, 2012. "A Green Vehicle Routing Problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 100-114.
    5. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "A review of recent research on green road freight transportation," European Journal of Operational Research, Elsevier, vol. 237(3), pages 775-793.
    6. Govindan, K. & Jafarian, A. & Khodaverdi, R. & Devika, K., 2014. "Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food," International Journal of Production Economics, Elsevier, vol. 152(C), pages 9-28.
    7. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2012. "An adaptive large neighborhood search heuristic for the Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 223(2), pages 346-359.
    8. Yunyun Niu & Zehua Yang & Rong Wen & Jianhua Xiao & Shuai Zhang, 2022. "Solving the Green Open Vehicle Routing Problem Using a Membrane-Inspired Hybrid Algorithm," Sustainability, MDPI, vol. 14(14), pages 1-22, July.
    9. Fuqiang Lu & Liying Wang & Hualing Bi & Zichao Du & Suxin Wang, 2021. "An Improved Revenue Distribution Model for Logistics Service Supply Chain Considering Fairness Preference," Sustainability, MDPI, vol. 13(12), pages 1-30, June.
    10. Archetti, Claudia & Savelsbergh, Martin & Speranza, M. Grazia, 2016. "The Vehicle Routing Problem with Occasional Drivers," European Journal of Operational Research, Elsevier, vol. 254(2), pages 472-480.
    11. Zhang, Jianghua & Zhao, Yingxue & Xue, Weili & Li, Jin, 2015. "Vehicle routing problem with fuel consumption and carbon emission," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 234-242.
    Full references (including those not matched with items on IDEAS)

    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. Emna Marrekchi & Walid Besbes & Diala Dhouib & Emrah Demir, 2021. "A review of recent advances in the operations research literature on the green routing problem and its variants," Annals of Operations Research, Springer, vol. 304(1), pages 529-574, September.
    2. Zhang, Shuai & Gajpal, Yuvraj & Appadoo, S.S. & Abdulkader, M.M.S., 2018. "Electric vehicle routing problem with recharging stations for minimizing energy consumption," International Journal of Production Economics, Elsevier, vol. 203(C), pages 404-413.
    3. Mohammad Asghari & Seyed Mohammad Javad Mirzapour Al-E-Hashem, 2021. "Green vehicle routing problem: A state-of-the-art review," Post-Print hal-03182944, HAL.
    4. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    5. Ozgur Kabadurmus & Mehmet S. Erdogan, 2023. "A green vehicle routing problem with multi-depot, multi-tour, heterogeneous fleet and split deliveries: a mathematical model and heuristic approach," Journal of Combinatorial Optimization, Springer, vol. 45(3), pages 1-29, April.
    6. Xiao, Yiyong & Zuo, Xiaorong & Huang, Jiaoying & Konak, Abdullah & Xu, Yuchun, 2020. "The continuous pollution routing problem," Applied Mathematics and Computation, Elsevier, vol. 387(C).
    7. Bektaş, Tolga & Ehmke, Jan Fabian & Psaraftis, Harilaos N. & Puchinger, Jakob, 2019. "The role of operational research in green freight transportation," European Journal of Operational Research, Elsevier, vol. 274(3), pages 807-823.
    8. Sam Heshmati & Jannes Verstichel & Eline Esprit & Greet Vanden Berghe, 2019. "Alternative e-commerce delivery policies," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(3), pages 217-248, September.
    9. Huang, Yixiao & Zhao, Lei & Van Woensel, Tom & Gross, Jean-Philippe, 2017. "Time-dependent vehicle routing problem with path flexibility," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 169-195.
    10. Herbert Kopfer & Benedikt Vornhusen, 2019. "Energy vehicle routing problem for differently sized and powered vehicles," Journal of Business Economics, Springer, vol. 89(7), pages 793-821, September.
    11. Liu, Yiming & Yu, Yang & Baldacci, Roberto & Tang, Jiafu & Sun, Wei, 2025. "Optimizing carbon emissions in green logistics for time-dependent routing," Transportation Research Part B: Methodological, Elsevier, vol. 192(C).
    12. Dukkanci, Okan & Karsu, Özlem & Kara, Bahar Y., 2022. "Planning sustainable routes: Economic, environmental and welfare concerns," European Journal of Operational Research, Elsevier, vol. 301(1), pages 110-123.
    13. Brunner, Carlos & Giesen, Ricardo & Klapp, Mathias A. & Flórez-Calderón, Luz, 2021. "Vehicle routing problem with steep roads," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 1-17.
    14. Goeke, Dominik & Schneider, Michael, 2015. "Routing a mixed fleet of electric and conventional vehicles," European Journal of Operational Research, Elsevier, vol. 245(1), pages 81-99.
    15. Behnke, Martin & Kirschstein, Thomas & Bierwirth, Christian, 2021. "A column generation approach for an emission-oriented vehicle routing problem on a multigraph," European Journal of Operational Research, Elsevier, vol. 288(3), pages 794-809.
    16. Jose Carlos Molina & Ignacio Eguia & Jesus Racero, 2019. "Reducing pollutant emissions in a waste collection vehicle routing problem using a variable neighborhood tabu search algorithm: a case study," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 253-287, July.
    17. Arslan, Okan & Yıldız, Barış & Karaşan, Oya Ekin, 2015. "Minimum cost path problem for Plug-in Hybrid Electric Vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 123-141.
    18. Goeke, D. & Schneider, M., 2015. "Routing a Mixed Fleet of Electric and Conventional Vehicles," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65939, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    19. Franceschetti, Anna & Demir, Emrah & Honhon, Dorothée & Van Woensel, Tom & Laporte, Gilbert & Stobbe, Mark, 2017. "A metaheuristic for the time-dependent pollution-routing problem," European Journal of Operational Research, Elsevier, vol. 259(3), pages 972-991.
    20. Sara Ceschia & Luca Di Gaspero & Antonella Meneghetti, 2020. "Extending and Solving the Refrigerated Routing Problem," Energies, MDPI, vol. 13(23), pages 1-24, November.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:comgts:v:22:y:2025:i:2:d:10.1007_s10287-025-00545-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.