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Planning of truck platooning for road-network capacitated vehicle routing problem

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  • Hao, Yilang
  • Chen, Zhibin
  • Sun, Xiaotong
  • Tong, Lu

Abstract

Truck platooning, a linking technology of trucks on the highway, has gained enormous attention in recent years due to its benefits in energy and operation cost savings. However, most existing studies on truck platooning limit their focus on particular scenarios that each truck can serve only one customer demand and is thus with a specified origin–destination pair, so only routing and time schedules are taken into account. Nevertheless, in real-world logistics, each truck may need to serve multiple customers located at different places, and the operator managing a fleet of trucks thus has to determine not only the routing and time schedules of each truck but also the set of customers allocated to each truck and their sequence to visit. This is well known as a capacitated vehicle routing problem with time windows (CVRPTW), and considering the application of truck platooning in such a problem entails new modeling frameworks and tailored solution algorithms. In light of this, this study makes the first attempt to optimize the truck platooning plan for a road-network CVRPTW in a way to minimize the total operation cost, including vehicles’ fixed dispatch cost and energy cost, while fulfilling all delivery demands within their time window constraints. Specifically, the operation plan will dictate the number of trucks to be dispatched, the set of customers, and the routing and time schedules for each truck. In addition, the modeling framework is constructed based on a road network instead of a traditional customer node graph to better resemble and facilitate the platooning operation. A 3-stage algorithm embedded with a ”route-then-schedule” scheme, Dynamic Programming, and Modified Insertion heuristic, is developed to solve the proposed model in a timely manner. Numerical experiments are conducted to validate the proposed modeling framework, demonstrate the performance of the proposed solution algorithm, and quantify the benefit brought by the truck platooning technology.

Suggested Citation

  • Hao, Yilang & Chen, Zhibin & Sun, Xiaotong & Tong, Lu, 2025. "Planning of truck platooning for road-network capacitated vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 194(C).
  • Handle: RePEc:eee:transe:v:194:y:2025:i:c:s1366554524004897
    DOI: 10.1016/j.tre.2024.103898
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    References listed on IDEAS

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    1. Yao, Yu & Van Woensel, Tom & Veelenturf, Lucas P. & Mo, Pengli, 2021. "The consistent vehicle routing problem considering path consistency in a road network," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 21-44.
    2. Sun, Xiaotong & Yin, Yafeng, 2021. "An auction mechanism for platoon leader determination in single-brand cooperative vehicle platooning," Economics of Transportation, Elsevier, vol. 28(C).
    3. Bhoopalam, Anirudh Kishore & Agatz, Niels & Zuidwijk, Rob, 2018. "Planning of truck platoons: A literature review and directions for future research," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 212-228.
    4. You, Jintao & Miao, Lixin & Zhang, Canrong & Xue, Zhaojie, 2020. "A generic model for the local container drayage problem using the emerging truck platooning operation mode," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 181-209.
    5. Yan, Xiaoyuan & Xu, Min & Xie, Chi, 2023. "Local container drayage problem with improved truck platooning operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    6. Boysen, Nils & Briskorn, Dirk & Schwerdfeger, Stefan, 2018. "The identical-path truck platooning problem," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 26-39.
    7. Abdolmaleki, Mojtaba & Shahabi, Mehrdad & Yin, Yafeng & Masoud, Neda, 2021. "Itinerary planning for cooperative truck platooning," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 91-110.
    8. Xue, Zhaojie & Lin, Hui & You, Jintao, 2021. "Local container drayage problem with truck platooning mode," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    9. Sun, Xiaotong & Yin, Yafeng, 2021. "Decentralized game-theoretical approaches for behaviorally-stable and efficient vehicle platooning," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 45-69.
    10. S. Sivanandham & M.S. Gajanand, 2022. "Comparison of platoon formations using departure time coordination heuristic," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 43(1/2), pages 96-118.
    11. Chen, Zhibin & He, Fang & Yin, Yafeng & Du, Yuchuan, 2017. "Optimal design of autonomous vehicle zones in transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 44-61.
    12. Chen, Zhibin & He, Fang & Yin, Yafeng, 2016. "Optimal deployment of charging lanes for electric vehicles in transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 344-365.
    13. Luca Accorsi & Daniele Vigo, 2021. "A Fast and Scalable Heuristic for the Solution of Large-Scale Capacitated Vehicle Routing Problems," Transportation Science, INFORMS, vol. 55(4), pages 832-856, July.
    14. Fengqiao Luo & Jeffrey Larson, 2022. "A Repeated Route-then-Schedule Approach to Coordinated Vehicle Platooning: Algorithms, Valid Inequalities and Computation," Operations Research, INFORMS, vol. 70(4), pages 2477-2495, July.
    15. Wolfinger, David & Salazar-González, Juan-José, 2021. "The Pickup and Delivery Problem with Split Loads and Transshipments: A Branch-and-Cut Solution Approach," European Journal of Operational Research, Elsevier, vol. 289(2), pages 470-484.
    16. Zhang, Wei & Jenelius, Erik & Ma, Xiaoliang, 2017. "Freight transport platoon coordination and departure time scheduling under travel time uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 98(C), pages 1-23.
    17. Marzano, Vittorio & Tinessa, Fiore & Fiori, Chiara & Tocchi, Daniela & Papola, Andrea & Aponte, Dario & Cascetta, Ennio & Simonelli, Fulvio, 2022. "Impacts of truck platooning on the multimodal freight transport market: An exploratory assessment on a case study in Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 100-125.
    18. Larsen, Rune & Rich, Jeppe & Rasmussen, Thomas Kjær, 2019. "Hub-based truck platooning: Potentials and profitability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 249-264.
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