IDEAS home Printed from https://ideas.repec.org/a/spr/joheur/v27y2021i5d10.1007_s10732-021-09481-1.html
   My bibliography  Save this article

An adaptive large neighbourhood search algorithm for diameter bounded network design problems

Author

Listed:
  • Michele Garraffa

    (University College Cork)

  • Deepak Mehta

    (University College Cork)

  • Barry O’Sullivan

    (University College Cork)

  • Cemalettin Ozturk

    (Munster Technological University, Process, Energy and Transport Engineering)

  • Luis Quesada

    (University College Cork)

Abstract

This paper focuses on designing a diameter - constrained network where the maximum distance between any pair of nodes is bounded. The objective considered is to minimise a weighted sum of the total length of the links followed by the total length of the paths between the pairs of nodes. First, the problem is formulated in terms of Mixed Integer Linear Programming and Constraint Programming to provide two alternative exact approaches. Then, an adaptive large neighbourhood search (LNS) to overcome memory and runtime limitations of the exact methods in large size instances is proposed. Such approach is based on computing an initial solution and repeatedly improve it by solving relatively small subproblems. We investigate various alternatives for finding an initial solution and propose two different heuristics for selecting subproblems. We have introduced a tighter lower bound, which demonstrates the quality of the solution obtained by the proposed approach. The performance of the proposed approach is assessed using three real-world network topologies from Ireland, UK and Italy, which are taken from national telecommunication operators and are used to design a transparent optical core network. Our results demonstrate that the LNS approach is scalable to large networks and it can compute very high quality solutions that are close to being optimal.

Suggested Citation

  • Michele Garraffa & Deepak Mehta & Barry O’Sullivan & Cemalettin Ozturk & Luis Quesada, 2021. "An adaptive large neighbourhood search algorithm for diameter bounded network design problems," Journal of Heuristics, Springer, vol. 27(5), pages 887-922, October.
    • Handle: RePEc:spr:joheur:v:27:y:2021:i:5:d:10.1007_s10732-021-09481-1
    DOI: 10.1007/s10732-021-09481-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10732-021-09481-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10732-021-09481-1?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. David Pisinger & Stefan Ropke, 2010. "Large Neighborhood Search," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 399-419, Springer.
    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. El Mehdi, Er Raqabi & Ilyas, Himmich & Nizar, El Hachemi & Issmaïl, El Hallaoui & François, Soumis, 2023. "Incremental LNS framework for integrated production, inventory, and vessel scheduling: Application to a global supply chain," Omega, Elsevier, vol. 116(C).
    2. Bach, Lukas & Hasle, Geir & Schulz, Christian, 2019. "Adaptive Large Neighborhood Search on the Graphics Processing Unit," European Journal of Operational Research, Elsevier, vol. 275(1), pages 53-66.
    3. Timo Hintsch, 2019. "Large Multiple Neighborhood Search for the Soft-Clustered Vehicle-Routing Problem," Working Papers 1904, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    4. Ulrike Ritzinger & Jakob Puchinger & Richard Hartl, 2016. "Dynamic programming based metaheuristics for the dial-a-ride problem," Annals of Operations Research, Springer, vol. 236(2), pages 341-358, January.
    5. Hatzenbühler, Jonas & Jenelius, Erik & Gidófalvi, Gyözö & Cats, Oded, 2023. "Modular vehicle routing for combined passenger and freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    6. Timo Gschwind & Michael Drexl, 2016. "Adaptive Large Neighborhood Search with a Constant-Time Feasibility Test for the Dial-a-Ride Problem," Working Papers 1624, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    7. Majid Eskandarpour & Pierre Dejax & Olivier Péton, 2019. "Multi-Directional Local Search for Sustainable Supply Chain Network Design," Post-Print hal-02407741, HAL.
    8. Daniela Guericke & Leena Suhl, 2017. "The home health care problem with working regulations," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 977-1010, October.
    9. Guido, Rosita & Groccia, Maria Carmela & Conforti, Domenico, 2018. "An efficient matheuristic for offline patient-to-bed assignment problems," European Journal of Operational Research, Elsevier, vol. 268(2), pages 486-503.
    10. Martina Fischetti & Michele Monaci, 2016. "Proximity search heuristics for wind farm optimal layout," Journal of Heuristics, Springer, vol. 22(4), pages 459-474, August.
    11. Efstratios Rappos & Eric Thiémard & Stephan Robert & Jean-François Hêche, 2022. "A mixed-integer programming approach for solving university course timetabling problems," Journal of Scheduling, Springer, vol. 25(4), pages 391-404, August.
    12. Marco Antonio Boschetti & Vittorio Maniezzo, 2022. "Matheuristics: using mathematics for heuristic design," 4OR, Springer, vol. 20(2), pages 173-208, June.
    13. Michael Drexl, 2018. "On the One-to-One Pickup-and-Delivery Problem with Time Windows and Trailers," Working Papers 1816, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    14. Ohad Eisenhandler & Michal Tzur, 2019. "The Humanitarian Pickup and Distribution Problem," Operations Research, INFORMS, vol. 67(1), pages 10-32, January.
    15. Lee, Jongsung & Kim, Byung-In & Johnson, Andrew L. & Lee, Kiho, 2014. "The nuclear medicine production and delivery problem," European Journal of Operational Research, Elsevier, vol. 236(2), pages 461-472.
    16. Ulrike Ritzinger & Jakob Puchinger & Richard F. Hartl, 2016. "Dynamic programming based metaheuristics for the dial-a-ride problem," Annals of Operations Research, Springer, vol. 236(2), pages 341-358, January.
    17. David Bulck & Dries R. Goossens & Frits C. R. Spieksma, 2019. "Scheduling a non-professional indoor football league: a tabu search based approach," Annals of Operations Research, Springer, vol. 275(2), pages 715-730, April.
    18. Amine Masmoudi, M. & Baldacci, Roberto & Mancini, Simona & Kuo, Yong-Hong, 2024. "Multi-compartment waste collection vehicle routing problem with bin washer," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 189(C).
    19. Wang, Zheng, 2018. "Delivering meals for multiple suppliers: Exclusive or sharing logistics service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 496-512.
    20. 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.

    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:spr:joheur:v:27:y:2021:i:5:d:10.1007_s10732-021-09481-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.