IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i2p1584-d1035168.html
   My bibliography  Save this article

Online Delivery Problem for Hybrid Truck–Drone System with Independent and Truck-Carried Drones

Author

Listed:
  • Mengyuan Gou

    (School of Economics and Management, Chongqing Jiaotong University, Nanan, Chongqing 400074, China)

  • Haiyan Yu

    (School of Economics and Management, Chongqing Jiaotong University, Nanan, Chongqing 400074, China)

Abstract

Considering real-time requests and multiple truck–drone delivery modes, we propose an online delivery problem using a truck and some drones, which form a hybrid truck–drone delivery collaboration system comprising independent and truck-carried drones. Considering this problem, we focus on how to schedule the vehicles to serve real-time requests, with the objective of minimizing the time of the latest vehicle’s return to the delivery station. First, we proved the lower bound of this problem to be 1.5. Second, we designed an online re-planning algorithm and proved its competitive ratio to be 2.5. As the online re-planning algorithm invokes an offline algorithm, an offline model was established, and an offline drone priority algorithm was designed. Then, we verified the effectiveness of the offline algorithm by comparing it with the CPLEX solution, and the stability of the online re-planning algorithm with different input parameters was studied through MATLAB simulation. Finally, the minimal latest time saving was calculated by comparing the hybrid truck–drone collaboration system with a truck-only delivery system. This research provides theoretical support for addressing the hybrid truck–drone delivery problem.

Suggested Citation

  • Mengyuan Gou & Haiyan Yu, 2023. "Online Delivery Problem for Hybrid Truck–Drone System with Independent and Truck-Carried Drones," Sustainability, MDPI, vol. 15(2), pages 1-15, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1584-:d:1035168
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/2/1584/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/2/1584/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Salama, Mohamed R. & Srinivas, Sharan, 2022. "Collaborative truck multi-drone routing and scheduling problem: Package delivery with flexible launch and recovery sites," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    2. Yu, Shaohua & Puchinger, Jakob & Sun, Shudong, 2022. "Van-based robot hybrid pickup and delivery routing problem," European Journal of Operational Research, Elsevier, vol. 298(3), pages 894-914.
    3. Patrick Jaillet & Michael R. Wagner, 2006. "Online Routing Problems: Value of Advanced Information as Improved Competitive Ratios," Transportation Science, INFORMS, vol. 40(2), pages 200-210, May.
    4. Yu, Wei & Liu, Zhaohui & Bao, Xiaoguang, 2014. "Optimal deterministic algorithms for some variants of Online Quota Traveling Salesman Problem," European Journal of Operational Research, Elsevier, vol. 238(3), pages 735-740.
    5. Xingang Wen & Yinfeng Xu & Huili Zhang, 2015. "Online traveling salesman problem with deadlines and service flexibility," Journal of Combinatorial Optimization, Springer, vol. 30(3), pages 545-562, October.
    6. Wang, Zheng & Sheu, Jiuh-Biing, 2019. "Vehicle routing problem with drones," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 350-364.
    7. Kloster, Konstantin & Moeini, Mahdi & Vigo, Daniele & Wendt, Oliver, 2023. "The multiple traveling salesman problem in presence of drone- and robot-supported packet stations," European Journal of Operational Research, Elsevier, vol. 305(2), pages 630-643.
    8. Asma Troudi & Sid-Ali Addouche & Sofiene Dellagi & Abderrahman El Mhamedi, 2018. "Sizing of the Drone Delivery Fleet Considering Energy Autonomy," Sustainability, MDPI, vol. 10(9), pages 1-17, September.
    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. Madani, Batool & Ndiaye, Malick & Salhi, Said, 2024. "Hybrid truck-drone delivery system with multi-visits and multi-launch and retrieval locations: Mathematical model and adaptive variable neighborhood search with neighborhood categorization," European Journal of Operational Research, Elsevier, vol. 316(1), pages 100-125.
    2. Meng, Shanshan & Chen, Yanru & Li, Dong, 2024. "The multi-visit drone-assisted pickup and delivery problem with time windows," European Journal of Operational Research, Elsevier, vol. 314(2), pages 685-702.
    3. 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.
    4. Yang Xia & Wenjia Zeng & Xinjie Xing & Yuanzhu Zhan & Kim Hua Tan & Ajay Kumar, 2023. "Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing," Annals of Operations Research, Springer, vol. 327(1), pages 89-127, August.
    5. Ren, Xuan & Froger, Aurélien & Jabali, Ola & Liang, Gongqian, 2024. "A competitive heuristic algorithm for vehicle routing problems with drones," European Journal of Operational Research, Elsevier, vol. 318(2), pages 469-485.
    6. Yu, Shaohua & Puchinger, Jakob & Sun, Shudong, 2024. "Electric van-based robot deliveries with en-route charging," European Journal of Operational Research, Elsevier, vol. 317(3), pages 806-826.
    7. Yin, Yunqiang & Li, Dongwei & Wang, Dujuan & Ignatius, Joshua & Cheng, T.C.E. & Wang, Sutong, 2023. "A branch-and-price-and-cut algorithm for the truck-based drone delivery routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1125-1144.
    8. Tiniç, Gizem Ozbaygin & Karasan, Oya E. & Kara, Bahar Y. & Campbell, James F. & Ozel, Aysu, 2023. "Exact solution approaches for the minimum total cost traveling salesman problem with multiple drones," Transportation Research Part B: Methodological, Elsevier, vol. 168(C), pages 81-123.
    9. Amine Masmoudi, M. & Mancini, Simona & Baldacci, Roberto & Kuo, Yong-Hong, 2022. "Vehicle routing problems with drones equipped with multi-package payload compartments," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    10. Shiri, Davood & Akbari, Vahid & Hassanzadeh, Ali, 2024. "The Capacitated Team Orienteering Problem: An online optimization framework with predictions of unknown accuracy," Transportation Research Part B: Methodological, Elsevier, vol. 185(C).
    11. Yin, Yunqiang & Yang, Yongjian & Yu, Yugang & Wang, Dujuan & Cheng, T.C.E., 2023. "Robust vehicle routing with drones under uncertain demands and truck travel times in humanitarian logistics," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    12. Xia, Yang & Zeng, Wenjia & Zhang, Canrong & Yang, Hai, 2023. "A branch-and-price-and-cut algorithm for the vehicle routing problem with load-dependent drones," Transportation Research Part B: Methodological, Elsevier, vol. 171(C), pages 80-110.
    13. Tengyu Wu & Lin He & Haiyan Yu, 0. "Online traveling salesman problem with time cost and non-zealous server," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-24.
    14. Zhou, Hang & Qin, Hu & Cheng, Chun & Rousseau, Louis-Martin, 2023. "An exact algorithm for the two-echelon vehicle routing problem with drones," Transportation Research Part B: Methodological, Elsevier, vol. 168(C), pages 124-150.
    15. Hu, Zhangchen & Chen, Heng & Lyons, Eric & Solak, Senay & Zink, Michael, 2024. "Towards sustainable UAV operations: Balancing economic optimization with environmental and social considerations in path planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    16. Sun, Xuting & Fang, Minghao & Guo, Shu & Hu, Yue, 2024. "UAV-rider coordinated dispatching for the on-demand delivery service provider," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    17. Nils Boysen & Stefan Fedtke & Stefan Schwerdfeger, 2021. "Last-mile delivery concepts: a survey from an operational research perspective," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 1-58, March.
    18. Liu, Zeyu & Li, Xueping & Khojandi, Anahita, 2022. "The flying sidekick traveling salesman problem with stochastic travel time: A reinforcement learning approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    19. Themistoklis Stamadianos & Nikolaos A. Kyriakakis & Magdalene Marinaki & Yannis Marinakis, 2023. "Routing Problems with Electric and Autonomous Vehicles: Review and Potential for Future Research," SN Operations Research Forum, Springer, vol. 4(2), pages 1-34, June.
    20. Tengyu Wu & Lin He & Haiyan Yu, 2022. "Online traveling salesman problem with time cost and non-zealous server," Journal of Combinatorial Optimization, Springer, vol. 44(3), pages 2143-2166, 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:gam:jsusta:v:15:y:2023:i:2:p:1584-:d:1035168. 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.