IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i5p2127-d330461.html
   My bibliography  Save this article

Solving the Multi-Depot Green Vehicle Routing Problem by a Hybrid Evolutionary Algorithm

Author

Listed:
  • Bo Peng

    (School of Business Administration, Southwestern University of Finance and Economics, Chengdu 610074, China)

  • Lifan Wu

    (School of Business Administration, Southwestern University of Finance and Economics, Chengdu 610074, China)

  • Yuxin Yi

    (College of Management, Sichuan Agricultural University, Chengdu 610074, China)

  • Xiding Chen

    (Department of Finance, Wenzhou Business College, Wenzhou 325035, China)

Abstract

The growing concerns about human pollution has motivated practitioners and researchers to focus on the environmental and social impacts of logistics and supply chains. In this paper, we consider the environmental impact of carbon dioxide emission on a vehicle routing problem with multiple depots. We present a hybrid evolutionary algorithm (HEA) to tackle it by combining a variable neighborhood search and an evolutionary algorithm. The proposed hybrid evolutionary algorithm includes several distinct features such as multiple neighborhood operators, a route-based crossover operator, and a distance- and quality-based population updating strategy. The results from our numerical experiments confirm the effectiveness and superiority of the proposed HEA in comparison with the best-performing methods in the literature and the public exact optimization solver CPLEX. Furthermore, an important aspect of the HEA is studied to assess its effect on the performance of the HEA.

Suggested Citation

  • Bo Peng & Lifan Wu & Yuxin Yi & Xiding Chen, 2020. "Solving the Multi-Depot Green Vehicle Routing Problem by a Hybrid Evolutionary Algorithm," Sustainability, MDPI, vol. 12(5), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:5:p:2127-:d:330461
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/5/2127/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/5/2127/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ubeda, S. & Arcelus, F.J. & Faulin, J., 2011. "Green logistics at Eroski: A case study," International Journal of Production Economics, Elsevier, vol. 131(1), pages 44-51, May.
    2. Joonyup Eun & Byung Duk Song & Sangbok Lee & Dae-Eun Lim, 2019. "Mathematical Investigation on the Sustainability of UAV Logistics," Sustainability, MDPI, vol. 11(21), pages 1-15, October.
    3. Bektas, Tolga & Laporte, Gilbert, 2011. "The Pollution-Routing Problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1232-1250, September.
    4. T. C. E. Cheng & Bo Peng & Zhipeng Lü, 2016. "A hybrid evolutionary algorithm to solve the job shop scheduling problem," Annals of Operations Research, Springer, vol. 242(2), pages 223-237, July.
    5. 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.
    6. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "The bi-objective Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 232(3), pages 464-478.
    7. Tiwari, Anurag & Chang, Pei-Chann, 2015. "A block recombination approach to solve green vehicle routing problem," International Journal of Production Economics, Elsevier, vol. 164(C), pages 379-387.
    8. Jinghua Li & Hui Guo & Qinghua Zhou & Boxin Yang, 2019. "Vehicle Routing and Scheduling Optimization of Ship Steel Distribution Center under Green Shipbuilding Mode," Sustainability, MDPI, vol. 11(15), pages 1-20, August.
    9. Yanjie Zhou & Gyu M. Lee, 2017. "A Lagrangian Relaxation-Based Solution Method for a Green Vehicle Routing Problem to Minimize Greenhouse Gas Emissions," Sustainability, MDPI, vol. 9(5), pages 1-17, May.
    10. Suzuki, Yoshinori, 2016. "A dual-objective metaheuristic approach to solve practical pollution routing problem," International Journal of Production Economics, Elsevier, vol. 176(C), pages 143-153.
    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. 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).
    2. 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.
    3. 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.
    4. Yu, Yang & Wu, Yuting & Wang, Junwei, 2019. "Bi-objective green ride-sharing problem: Model and exact method," International Journal of Production Economics, Elsevier, vol. 208(C), pages 472-482.
    5. Kramer, Raphael & Subramanian, Anand & Vidal, Thibaut & Cabral, Lucídio dos Anjos F., 2015. "A matheuristic approach for the Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 243(2), pages 523-539.
    6. 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.
    7. Heilig, Leonard & Lalla-Ruiz, Eduardo & Voß, Stefan, 2017. "Multi-objective inter-terminal truck routing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 178-202.
    8. Turkensteen, Marcel, 2017. "The accuracy of carbon emission and fuel consumption computations in green vehicle routing," European Journal of Operational Research, Elsevier, vol. 262(2), pages 647-659.
    9. 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.
    10. 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.
    11. Raeesi, Ramin & Zografos, Konstantinos G., 2019. "The multi-objective Steiner pollution-routing problem on congested urban road networks," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 457-485.
    12. Soysal, Mehmet & Bloemhof-Ruwaard, Jacqueline M. & Bektaş, Tolga, 2015. "The time-dependent two-echelon capacitated vehicle routing problem with environmental considerations," International Journal of Production Economics, Elsevier, vol. 164(C), pages 366-378.
    13. 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.
    14. Xiao, Yiyong & Zuo, Xiaorong & Huang, Jiaoying & Konak, Abdullah & Xu, Yuchun, 2020. "The continuous pollution routing problem," Applied Mathematics and Computation, Elsevier, vol. 387(C).
    15. Chiang, Wen-Chyuan & Li, Yuyu & Shang, Jennifer & Urban, Timothy L., 2019. "Impact of drone delivery on sustainability and cost: Realizing the UAV potential through vehicle routing optimization," Applied Energy, Elsevier, vol. 242(C), pages 1164-1175.
    16. Qian, Jiani & Eglese, Richard, 2016. "Fuel emissions optimization in vehicle routing problems with time-varying speeds," European Journal of Operational Research, Elsevier, vol. 248(3), pages 840-848.
    17. Yagcitekin, Bunyamin & Uzunoglu, Mehmet, 2016. "A double-layer smart charging strategy of electric vehicles taking routing and charge scheduling into account," Applied Energy, Elsevier, vol. 167(C), pages 407-419.
    18. Tricoire, Fabien & Parragh, Sophie N., 2017. "Investing in logistics facilities today to reduce routing emissions tomorrow," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 56-67.
    19. Suzuki, Yoshinori, 2016. "A dual-objective metaheuristic approach to solve practical pollution routing problem," International Journal of Production Economics, Elsevier, vol. 176(C), pages 143-153.
    20. 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.

    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:gam:jsusta:v:12:y:2020:i:5:p:2127-:d:330461. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.