IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v285y2020i3p844-852.html
   My bibliography  Save this article

On optimal coverage of a tree with multiple robots

Author

Listed:
  • Aldana-Galván, I.
  • Catana-Salazar, J.C.
  • Díaz-Báñez, J.M.
  • Duque, F.
  • Fabila-Monroy, R.
  • Heredia, M.A.
  • Ramírez-Vigueras, A.
  • Urrutia, J.

Abstract

We study the algorithmic problem of optimally covering a tree with k mobile robots. The tree is known to all robots, and our goal is to assign a walk to each robot in such a way that the union of these walks covers the whole tree. We assume that the edges have the same length, and that traveling along an edge takes a unit of time. Two objective functions are considered: the cover time and the cover length. The cover time is the maximum time a robot needs to finish its assigned walk and the cover length is the sum of the lengths of all the walks. We also consider a variant in which the robots must rendezvous periodically at the same vertex in at most a certain number of moves. We show that the problem is different for the two cost functions. For the cover time minimization problem, we prove that the problem is NP-hard when k is part of the input, regardless of whether periodic rendezvous are required or not. For the cover length minimization problem, we show that it can be solved in polynomial time when periodic rendezvous are not required, and it is NP-hard otherwise.

Suggested Citation

  • Aldana-Galván, I. & Catana-Salazar, J.C. & Díaz-Báñez, J.M. & Duque, F. & Fabila-Monroy, R. & Heredia, M.A. & Ramírez-Vigueras, A. & Urrutia, J., 2020. "On optimal coverage of a tree with multiple robots," European Journal of Operational Research, Elsevier, vol. 285(3), pages 844-852.
  • Handle: RePEc:eee:ejores:v:285:y:2020:i:3:p:844-852
    DOI: 10.1016/j.ejor.2020.02.035
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221720301703
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2020.02.035?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. 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.
    2. Bektas, Tolga, 2006. "The multiple traveling salesman problem: an overview of formulations and solution procedures," Omega, Elsevier, vol. 34(3), pages 209-219, June.
    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.
    4. Nagy, Gabor & Salhi, Said, 2007. "Location-routing: Issues, models and methods," European Journal of Operational Research, Elsevier, vol. 177(2), pages 649-672, March.
    5. G. Clarke & J. W. Wright, 1964. "Scheduling of Vehicles from a Central Depot to a Number of Delivery Points," Operations Research, INFORMS, vol. 12(4), pages 568-581, August.
    6. Sergey Bereg & Luis-Evaristo Caraballo & José-Miguel Díaz-Báñez & Mario A. Lopez, 2018. "Computing the k-resilience of a synchronized multi-robot system," Journal of Combinatorial Optimization, Springer, vol. 36(2), pages 365-391, August.
    7. Gilbert Laporte, 2009. "Fifty Years of Vehicle Routing," Transportation Science, INFORMS, vol. 43(4), pages 408-416, November.
    8. Fliege, Jörg & Kaparis, Konstantinos & Khosravi, Banafsheh, 2012. "Operations research in the space industry," European Journal of Operational Research, Elsevier, vol. 217(2), pages 233-240.
    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. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2013. "Heuristics for multi-attribute vehicle routing problems: A survey and synthesis," European Journal of Operational Research, Elsevier, vol. 231(1), pages 1-21.
    2. Qiuping Ni & Yuanxiang Tang, 2023. "A Bibliometric Visualized Analysis and Classification of Vehicle Routing Problem Research," Sustainability, MDPI, vol. 15(9), pages 1-37, April.
    3. Fleming, Christopher L. & Griffis, Stanley E. & Bell, John E., 2013. "The effects of triangle inequality on the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 224(1), pages 1-7.
    4. Frank, Markus & Ostermeier, Manuel & Holzapfel, Andreas & Hübner, Alexander & Kuhn, Heinrich, 2021. "Optimizing routing and delivery patterns with multi-compartment vehicles," European Journal of Operational Research, Elsevier, vol. 293(2), pages 495-510.
    5. Menezes, Mozart B.C. & Ruiz-Hernández, Diego & Verter, Vedat, 2016. "A rough-cut approach for evaluating location-routing decisions via approximation algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 87(C), pages 89-106.
    6. Kim, Nayeon & Montreuil, Benoit & Klibi, Walid & Kholgade, Nitish, 2021. "Hyperconnected urban fulfillment and delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    7. Brandstätter, Christian & Reimann, Marc, 2018. "The Line-haul Feeder Vehicle Routing Problem: Mathematical model formulation and heuristic approaches," European Journal of Operational Research, Elsevier, vol. 270(1), pages 157-170.
    8. 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.
    9. Mohamed Cissé & Semih Yalçindag & Yannick Kergosien & Evren Sahin & Christophe Lenté & Andrea Matta, 2017. "OR problems related to Home Health Care: A review of relevant routing and scheduling problems," Post-Print hal-01736714, HAL.
    10. Wang, Yong & Peng, Shouguo & Zhou, Xuesong & Mahmoudi, Monirehalsadat & Zhen, Lu, 2020. "Green logistics location-routing problem with eco-packages," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    11. Du, Jiaoman & Zhou, Jiandong & Li, Xiang & Li, Lei & Guo, Ao, 2021. "Integrated self-driving travel scheme planning," International Journal of Production Economics, Elsevier, vol. 232(C).
    12. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "The fleet size and mix location-routing problem with time windows: Formulations and a heuristic algorithm," European Journal of Operational Research, Elsevier, vol. 248(1), pages 33-51.
    13. Rieck, Julia & Ehrenberg, Carsten & Zimmermann, Jürgen, 2014. "Many-to-many location-routing with inter-hub transport and multi-commodity pickup-and-delivery," European Journal of Operational Research, Elsevier, vol. 236(3), pages 863-878.
    14. Hideki Hashimoto & Mutsunori Yagiura & Shinji Imahori & Toshihide Ibaraki, 2013. "Recent progress of local search in handling the time window constraints of the vehicle routing problem," Annals of Operations Research, Springer, vol. 204(1), pages 171-187, April.
    15. Lagos, Felipe & Pereira, Jordi, 2024. "Multi-armed bandit-based hyper-heuristics for combinatorial optimization problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 70-91.
    16. 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.
    17. Funke, Julia & Kopfer, Herbert, 2016. "A model for a multi-size inland container transportation problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 70-85.
    18. Liu, Ran & Jiang, Zhibin, 2012. "The close–open mixed vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 220(2), pages 349-360.
    19. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "Thirty years of heterogeneous vehicle routing," European Journal of Operational Research, Elsevier, vol. 249(1), pages 1-21.
    20. 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.

    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:ejores:v:285:y:2020:i:3:p:844-852. 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/locate/eor .

    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.