IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i2p326-d306849.html
   My bibliography  Save this article

Cooperative Transmission Tower Inspection with a Vehicle and a UAV in Urban Areas

Author

Listed:
  • Ju Wang

    (School of Management, Hefei University of Technology, Hefei 230009, China
    Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China)

  • Guoqiang Wang

    (School of Management, Hefei University of Technology, Hefei 230009, China
    Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China
    Engineering Research Center for Intelligent Decision-making & Information Systems Technologies, Ministry of Education, Hefei 230009, China)

  • Xiaoxuan Hu

    (School of Management, Hefei University of Technology, Hefei 230009, China
    Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China
    Engineering Research Center for Intelligent Decision-making & Information Systems Technologies, Ministry of Education, Hefei 230009, China)

  • He Luo

    (School of Management, Hefei University of Technology, Hefei 230009, China
    Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China
    Engineering Research Center for Intelligent Decision-making & Information Systems Technologies, Ministry of Education, Hefei 230009, China)

  • Haiqing Xu

    (Anhui Jiyuan Software CO., Ltd., Hefei 230088, China)

Abstract

To reduce the workload of inspectors and improve the inspection efficiency of urban transmission towers, a new inspection method is proposed in this paper, in which an unmanned aerial vehicle (UAV) and vehicle cooperate with each other. We investigate the cooperative path planning problem of a UAV and a vehicle for transmission tower inspection and develop a new 0–1 integer programming model to address the problem. An odd-even layered genetic algorithm (O-ELGA) is proposed to efficiently solve the model. Finally, the effectiveness of the algorithm is further verified by simulation experiments.

Suggested Citation

  • Ju Wang & Guoqiang Wang & Xiaoxuan Hu & He Luo & Haiqing Xu, 2020. "Cooperative Transmission Tower Inspection with a Vehicle and a UAV in Urban Areas," Energies, MDPI, vol. 13(2), pages 1-17, January.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:2:p:326-:d:306849
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/2/326/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/2/326/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Haiyan Cheng & Yongjie Zhai & Rui Chen & Di Wang & Ze Dong & Yutao Wang, 2019. "Self-Shattering Defect Detection of Glass Insulators Based on Spatial Features," Energies, MDPI, vol. 12(3), pages 1-14, February.
    2. Niels Agatz & Paul Bouman & Marie Schmidt, 2018. "Optimization Approaches for the Traveling Salesman Problem with Drone," Transportation Science, INFORMS, vol. 52(4), pages 965-981, August.
    3. 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.
    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. Jianxun Li & Hao Liu & Kin Keung Lai & Bhagwat Ram, 2022. "Vehicle and UAV Collaborative Delivery Path Optimization Model," Mathematics, MDPI, vol. 10(20), pages 1-22, October.
    2. Hailong Huang & Andrey V. Savkin, 2020. "Energy-Efficient Autonomous Navigation of Solar-Powered UAVs for Surveillance of Mobile Ground Targets in Urban Environments," Energies, MDPI, vol. 13(21), pages 1-17, October.
    3. Hailong Huang & Andrey V. Savkin & Wei Ni, 2020. "Energy-Efficient 3D Navigation of a Solar-Powered UAV for Secure Communication in the Presence of Eavesdroppers and No-Fly Zones," Energies, MDPI, vol. 13(6), pages 1-12, March.

    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. Chen, Cheng & Demir, Emrah & Huang, Yuan, 2021. "An adaptive large neighborhood search heuristic for the vehicle routing problem with time windows and delivery robots," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1164-1180.
    2. 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.
    3. Jianxun Li & Hao Liu & Kin Keung Lai & Bhagwat Ram, 2022. "Vehicle and UAV Collaborative Delivery Path Optimization Model," Mathematics, MDPI, vol. 10(20), pages 1-22, October.
    4. Pei, Zhi & Dai, Xu & Yuan, Yilun & Du, Rui & Liu, Changchun, 2021. "Managing price and fleet size for courier service with shared drones," Omega, Elsevier, vol. 104(C).
    5. Jacek Buko & Marek Bulsa & Adam Makowski, 2022. "Spatial Premises and Key Conditions for the Use of UAVs for Delivery of Items on the Example of the Polish Courier and Postal Services Market," Energies, MDPI, vol. 15(4), pages 1-17, February.
    6. Yichen Lu & Chao Yang & Jun Yang, 2022. "A multi-objective humanitarian pickup and delivery vehicle routing problem with drones," Annals of Operations Research, Springer, vol. 319(1), pages 291-353, December.
    7. Qiqian Zhang & Xiao Huang & Honghai Zhang & Chunyun He, 2023. "Research on Logistics Path Optimization for a Two-Stage Collaborative Delivery System Using Vehicles and UAVs," Sustainability, MDPI, vol. 15(17), pages 1-20, September.
    8. Stefan Poikonen & Bruce Golden, 2020. "The Mothership and Drone Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 249-262, April.
    9. 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.
    10. 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.
    11. Anna Kwasiborska & Anna Stelmach & Izabela Jabłońska, 2023. "Quantitative and Comparative Analysis of Energy Consumption in Urban Logistics Using Unmanned Aerial Vehicles and Selected Means of Transport," Energies, MDPI, vol. 16(18), pages 1-27, September.
    12. Zahid Ali Siddiqui & Unsang Park, 2020. "A Drone Based Transmission Line Components Inspection System with Deep Learning Technique," Energies, MDPI, vol. 13(13), pages 1-24, June.
    13. 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.
    14. Tengkuo Zhu & Stephen D. Boyles & Avinash Unnikrishnan, 2024. "Battery Electric Vehicle Traveling Salesman Problem with Drone," Networks and Spatial Economics, Springer, vol. 24(1), pages 49-97, March.
    15. Vincent F. Yu & Shih-Wei Lin & Panca Jodiawan & Yu-Chi Lai, 2023. "Solving the Flying Sidekick Traveling Salesman Problem by a Simulated Annealing Heuristic," Mathematics, MDPI, vol. 11(20), pages 1-21, October.
    16. Snežana Tadić & Mladen Krstić & Ljubica Radovanović, 2024. "Assessing Strategies to Overcome Barriers for Drone Usage in Last-Mile Logistics: A Novel Hybrid Fuzzy MCDM Model," Mathematics, MDPI, vol. 12(3), pages 1-25, January.
    17. Mohammad Moshref-Javadi & Kristof P. Cauwenberghe & Brent A. McCunney & Ahmad Hemmati, 2023. "Enabling same-day delivery using a drone resupply model with transshipment points," Computational Management Science, Springer, vol. 20(1), pages 1-31, December.
    18. 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.
    19. Jeong, Ho Young & Yu, David J. & Min, Byung-Cheol & Lee, Seokcheon, 2020. "The humanitarian flying warehouse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    20. Zhao, Lei & Bi, Xinhua & Li, Gendao & Dong, Zhaohui & Xiao, Ni & Zhao, Anni, 2022. "Robust traveling salesman problem with multiple drones: Parcel delivery under uncertain navigation environments," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).

    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:jeners:v:13:y:2020:i:2:p:326-:d:306849. 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.