IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i11p4829-d1663253.html

Time-Dependent Vehicle Routing Optimization Incorporating Pollution Reduction Using Hybrid Gray Wolf Optimizer and Neural Networks

Author

Listed:
  • Zhongneng Ma

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China)

  • Ching-Tsung Jen

    (Department of Global Business, Chinese Culture University, Taipei 111396, Taiwan)

  • Adel Aazami

    (Institute for Transport and Logistics Management, Department of Global Business and Trade, Vienna University of Economics and Business, 1020 Vienna, Austria)

Abstract

Road transport is a major contributor to air pollution, necessitating sustainable solutions for urban logistics. This study presents a time-dependent vehicle routing problem (VRP) model aimed at minimizing fuel consumption and greenhouse gas emissions while addressing stochastic customer demands. By incorporating key environmental factors such as road gradients, vehicle load, temperature, wind direction, and asphalt type, the proposed model provides a comprehensive approach to reducing transportation-related pollutants. To solve the computationally complex problem, a hybrid algorithm combining the gray wolf optimizer (GWO) and the multilayer perceptron (MLP) neural network is introduced. The algorithm demonstrates superior performance, achieving an error rate of less than 2% for medium-scale problems and significantly reducing fuel and driver costs. Sensitivity analyses reveal the profound impact of environmental parameters, with wind speed and direction altering optimal routing in over 80% of cases for large-scale instances. This research advances green logistics by integrating dynamic environmental considerations into routing decisions, balancing economic objectives with sustainability. The proposed model and algorithm offer a scalable solution to real-world challenges, enabling policymakers and logistics planners to improve environmental outcomes while maintaining operational efficiency.

Suggested Citation

  • Zhongneng Ma & Ching-Tsung Jen & Adel Aazami, 2025. "Time-Dependent Vehicle Routing Optimization Incorporating Pollution Reduction Using Hybrid Gray Wolf Optimizer and Neural Networks," Sustainability, MDPI, vol. 17(11), pages 1-27, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:11:p:4829-:d:1663253
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/11/4829/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/11/4829/
    Download Restriction: no
    ---><---

    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. Yu Li & Xiaoxiao Lin & Jingsen Liu, 2021. "An Improved Gray Wolf Optimization Algorithm to Solve Engineering Problems," Sustainability, MDPI, vol. 13(6), pages 1-23, March.
    3. 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.
    4. Ramos, Tânia Rodrigues Pereira & Gomes, Maria Isabel & Barbosa-Póvoa, Ana Paula, 2014. "Economic and environmental concerns in planning recyclable waste collection systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 34-54.
    5. Erfan Babaee Tirkolaee & Alireza Goli & Abbas Mardani, 2023. "A novel two-echelon hierarchical location-allocation-routing optimization for green energy-efficient logistics systems," Annals of Operations Research, Springer, vol. 324(1), pages 795-823, May.
    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. Ishumbaev, Konstantin & Zhu, Zhen & Ileye, Yasin & Armah, Abdul Karim, 2025. "Consumer behavior and market substitution in the automobile retail sectors of Russia and China amidst global economic sanctions and uncertainty," Journal of Retailing and Consumer Services, Elsevier, vol. 87(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. Ehmke, Jan Fabian & Campbell, Ann M. & Thomas, Barrett W., 2018. "Optimizing for total costs in vehicle routing in urban areas," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 242-265.
    2. Hamed Farrokhi-Asl & Ahmad Makui & Armin Jabbarzadeh & Farnaz Barzinpour, 2020. "Solving a multi-objective sustainable waste collection problem considering a new collection network," Operational Research, Springer, vol. 20(4), pages 1977-2015, December.
    3. 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).
    4. Arjun Paul & Ravi Shankar Kumar & Chayanika Rout & Adrijit Goswami, 2021. "A bi-objective two-echelon pollution routing problem with simultaneous pickup and delivery under multiple time windows constraint," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 962-993, December.
    5. Kramer, Raphael & Maculan, Nelson & Subramanian, Anand & Vidal, Thibaut, 2015. "A speed and departure time optimization algorithm for the pollution-routing problem," European Journal of Operational Research, Elsevier, vol. 247(3), pages 782-787.
    6. Xiao, Yiyong & Konak, Abdullah, 2016. "The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 146-166.
    7. 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.
    8. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "The impact of depot location, fleet composition and routing on emissions in city logistics," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 81-102.
    9. 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.
    10. Kirschstein, Thomas & Meisel, Frank, 2015. "GHG-emission models for assessing the eco-friendliness of road and rail freight transports," Transportation Research Part B: Methodological, Elsevier, vol. 73(C), pages 13-33.
    11. 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.
    12. Nasreddine Ouertani & Hajer Ben-Romdhane & Saoussen Krichen & Issam Nouaouri, 2022. "A vector evaluated evolutionary algorithm with exploitation reinforcement for the dynamic pollution routing problem," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1011-1038, September.
    13. Ehmke, Jan Fabian & Campbell, Ann Melissa & Thomas, Barrett W., 2016. "Vehicle routing to minimize time-dependent emissions in urban areas," European Journal of Operational Research, Elsevier, vol. 251(2), pages 478-494.
    14. Çağrı Koç, 2019. "Analysis of vehicle emissions in location-routing problem," Flexible Services and Manufacturing Journal, Springer, vol. 31(1), pages 1-33, March.
    15. Carlos A. Vega-Mejía & Jairo R. Montoya-Torres & Sardar M. N. Islam, 2019. "Consideration of triple bottom line objectives for sustainability in the optimization of vehicle routing and loading operations: a systematic literature review," Annals of Operations Research, Springer, vol. 273(1), pages 311-375, February.
    16. 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.
    17. 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.
    18. Qiu, Rui & Xu, Jiuping & Ke, Ruimin & Zeng, Ziqiang & Wang, Yinhai, 2020. "Carbon pricing initiatives-based bi-level pollution routing problem," European Journal of Operational Research, Elsevier, vol. 286(1), pages 203-217.
    19. 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.
    20. 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.

    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:gam:jsusta:v:17:y:2025:i:11:p:4829-:d:1663253. 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 The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (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.