IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v184y2023ics1364032123003830.html
   My bibliography  Save this article

A dynamic approach for the multi-compartment vehicle routing problem in waste management

Author

Listed:
  • Mohammadi, Mostafa
  • Rahmanifar, Golman
  • Hajiaghaei-Keshteli, Mostafa
  • Fusco, Gaetano
  • Colombaroni, Chiara
  • Sherafat, Ali

Abstract

Urban areas worldwide face a significant environmental challenge which is increasing municipal solid waste rate. Addressing its negative consequences necessitates advancements in waste management systems. Although the previous research focused on the static routing approach in the collection phase, this paper adds a dynamic municipal solid waste collection scheme to optimize vehicle routing, accounting for fluctuations in waste generation and changes in transportation systems. This study employs, for the first time, the application of a discrete choice model (DCM) to streamline the process of re-optimization in dynamic vehicle routing problems (DVRP). At each decision epoch, DCM is applied to determine the likelihood of choosing the next geographical zone to visit bins based on current waste generation levels and traveling costs. Moreover, the multi-compartment vehicles are considered to preserve waste segregation during transportation, thereby increasing operational efficiency and regulatory compliance. Another contribution of this paper is to determine visiting priority for each bin by adjusting the time window based on the threshold waste level. Hence, this paper proposes a framework for sustainable, efficient, and effective waste management practices by integrating the benefits of dynamic and multi-compartment routing. Furthermore, a hybrid Genetic and Particle Swarm Optimization algorithm has been designed to find the best solution for the studied problem as well as some of the latest and most proficient metaheuristic algorithms. Finally, the Best Worst Method is applied to find the best-proposed algorithm to solve the presented problem, indicating that the hybrid algorithm has the highest performance in providing high-quality route plans.

Suggested Citation

  • Mohammadi, Mostafa & Rahmanifar, Golman & Hajiaghaei-Keshteli, Mostafa & Fusco, Gaetano & Colombaroni, Chiara & Sherafat, Ali, 2023. "A dynamic approach for the multi-compartment vehicle routing problem in waste management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    • Handle: RePEc:eee:rensus:v:184:y:2023:i:c:s1364032123003830
    DOI: 10.1016/j.rser.2023.113526
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032123003830
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2023.113526?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. Maryam Abdirad & Krishna Krishnan & Deepak Gupta, 2021. "A two-stage metaheuristic algorithm for the dynamic vehicle routing problem in Industry 4.0 approach," Journal of Management Analytics, Taylor & Francis Journals, vol. 8(1), pages 69-83, January.
    2. Said Dabia & Stefan Ropke & Tom van Woensel & Ton De Kok, 2013. "Branch and Price for the Time-Dependent Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 47(3), pages 380-396, August.
    3. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    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. Nicolas Rincon-Garcia & Ben J. Waterson & Tom J. Cherrett, 2018. "Requirements from vehicle routing software: perspectives from literature, developers and the freight industry," Transport Reviews, Taylor & Francis Journals, vol. 38(1), pages 117-138, January.
    2. Babagolzadeh, Mahla & Zhang, Yahua & Abbasi, Babak & Shrestha, Anup & Zhang, Anming, 2022. "Promoting Australian regional airports with subsidy schemes: Optimised downstream logistics using vehicle routing problem," Transport Policy, Elsevier, vol. 128(C), pages 38-51.
    3. Aarabi, Fatemeh & Batta, Rajan, 2020. "Scheduling spatially distributed jobs with degradation: Application to pothole repair," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    4. Yao, Yu & Zhu, Xiaoning & Dong, Hongyu & Wu, Shengnan & Wu, Hailong & Carol Tong, Lu & Zhou, Xuesong, 2019. "ADMM-based problem decomposition scheme for vehicle routing problem with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 156-174.
    5. Liu, Yiming & Roberto, Baldacci & Zhou, Jianwen & Yu, Yang & Zhang, Yu & Sun, Wei, 2023. "Efficient feasibility checks and an adaptive large neighborhood search algorithm for the time-dependent green vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 310(1), pages 133-155.
    6. Said Dabia & Emrah Demir & Tom Van Woensel, 2017. "An Exact Approach for a Variant of the Pollution-Routing Problem," Transportation Science, INFORMS, vol. 51(2), pages 607-628, May.
    7. Ozbaygin, Gizem & Ekin Karasan, Oya & Savelsbergh, Martin & Yaman, Hande, 2017. "A branch-and-price algorithm for the vehicle routing problem with roaming delivery locations," Transportation Research Part B: Methodological, Elsevier, vol. 100(C), pages 115-137.
    8. Özarık, Sami Serkan & Veelenturf, Lucas P. & Woensel, Tom Van & Laporte, Gilbert, 2021. "Optimizing e-commerce last-mile vehicle routing and scheduling under uncertain customer presence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    9. Zhixing Luo & Hu Qin & Wenbin Zhu & Andrew Lim, 2017. "Branch and Price and Cut for the Split-Delivery Vehicle Routing Problem with Time Windows and Linear Weight-Related Cost," Transportation Science, INFORMS, vol. 51(2), pages 668-687, May.
    10. Rincon-Garcia, Nicolas & Waterson, Ben & Cherrett, Tom J. & Salazar-Arrieta, Fernando, 2020. "A metaheuristic for the time-dependent vehicle routing problem considering driving hours regulations – An application in city logistics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 429-446.
    11. Sun, Peng & Veelenturf, Lucas P. & Hewitt, Mike & Van Woensel, Tom, 2020. "Adaptive large neighborhood search for the time-dependent profitable pickup and delivery problem with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    12. Yi-Kuei Lin & Cheng-Fu Huang & Yi-Chieh Liao, 2019. "Reliability of a stochastic intermodal logistics network under spoilage and time considerations," Annals of Operations Research, Springer, vol. 277(1), pages 95-118, June.
    13. Filippo Focacci & Andrea Lodi & Michela Milano, 2002. "A Hybrid Exact Algorithm for the TSPTW," INFORMS Journal on Computing, INFORMS, vol. 14(4), pages 403-417, November.
    14. Zhang, Ying & Qi, Mingyao & Miao, Lixin & Liu, Erchao, 2014. "Hybrid metaheuristic solutions to inventory location routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 305-323.
    15. Lu, Quan & Dessouky, Maged M., 2006. "A new insertion-based construction heuristic for solving the pickup and delivery problem with time windows," European Journal of Operational Research, Elsevier, vol. 175(2), pages 672-687, December.
    16. Sébastien Mouthuy & Florence Massen & Yves Deville & Pascal Van Hentenryck, 2015. "A Multistage Very Large-Scale Neighborhood Search for the Vehicle Routing Problem with Soft Time Windows," Transportation Science, INFORMS, vol. 49(2), pages 223-238, May.
    17. Cheng, Chun & Adulyasak, Yossiri & Rousseau, Louis-Martin, 2020. "Drone routing with energy function: Formulation and exact algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 364-387.
    18. Gutiérrez-Jarpa, Gabriel & Desaulniers, Guy & Laporte, Gilbert & Marianov, Vladimir, 2010. "A branch-and-price algorithm for the Vehicle Routing Problem with Deliveries, Selective Pickups and Time Windows," European Journal of Operational Research, Elsevier, vol. 206(2), pages 341-349, October.
    19. Ann-Kathrin Rothenbächer & Michael Drexl & Stefan Irnich, 2018. "Branch-and-Price-and-Cut for the Truck-and-Trailer Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 52(5), pages 1174-1190, October.
    20. Luigi Di Puglia Pugliese & Francesca Guerriero & Maria Grazia Scutellá, 2021. "The Last-Mile Delivery Process with Trucks and Drones Under Uncertain Energy Consumption," Journal of Optimization Theory and Applications, Springer, vol. 191(1), pages 31-67, October.

    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:rensus:v:184:y:2023:i:c:s1364032123003830. 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/600126/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.