IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i20p4361-d1263859.html
   My bibliography  Save this article

A Population-Based Local Search Algorithm for the Identifying Code Problem

Author

Listed:
  • Alejandro Lara-Caballero

    (Department of Applied Mathematics and Systems, Universidad Autónoma Metropolitana, Cuajimalpa, Mexico City 05348, Mexico)

  • Diego González-Moreno

    (Department of Applied Mathematics and Systems, Universidad Autónoma Metropolitana, Cuajimalpa, Mexico City 05348, Mexico)

Abstract

The identifying code problem for a given graph involves finding a minimum subset of vertices such that each vertex of the graph is uniquely specified by its nonempty neighborhood within the identifying code. The combinatorial optimization problem has a wide variety of applications in location and detection schemes. Finding an identifying code of minimum possible size is a difficult task. In fact, it has been proven to be computationally intractable (NP-complete). Therefore, the use of heuristics to provide good approximations in a reasonable amount of time is justified. In this work, we present a new population-based local search algorithm for finding identifying codes of minimum cost. Computational experiments show that the proposed approach was found to be more effective than other state-of-the-art algorithms at generating high-quality solutions in different types of graphs with varying numbers of vertices.

Suggested Citation

  • Alejandro Lara-Caballero & Diego González-Moreno, 2023. "A Population-Based Local Search Algorithm for the Identifying Code Problem," Mathematics, MDPI, vol. 11(20), pages 1-17, October.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:20:p:4361-:d:1263859
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/20/4361/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/20/4361/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Beasley, J. E., 1987. "An algorithm for set covering problem," European Journal of Operational Research, Elsevier, vol. 31(1), pages 85-93, July.
    2. Wang, Yiyuan & Pan, Shiwei & Al-Shihabi, Sameh & Zhou, Junping & Yang, Nan & Yin, Minghao, 2021. "An improved configuration checking-based algorithm for the unicost set covering problem," European Journal of Operational Research, Elsevier, vol. 294(2), pages 476-491.
    3. Yupeng Zhou & Jinshu Li & Yang Liu & Shuai Lv & Yong Lai & Jianan Wang, 2020. "Improved Memetic Algorithm for Solving the Minimum Weight Vertex Independent Dominating Set," Mathematics, MDPI, vol. 8(7), pages 1-17, July.
    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. Helena R. Lourenço & José P. Paixão & Rita Portugal, 2001. "Multiobjective Metaheuristics for the Bus Driver Scheduling Problem," Transportation Science, INFORMS, vol. 35(3), pages 331-343, August.
    2. Lan, Guanghui & DePuy, Gail W. & Whitehouse, Gary E., 2007. "An effective and simple heuristic for the set covering problem," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1387-1403, February.
    3. Mete Suleyman & Cil Zeynel Abidin & Özceylan Eren, 2018. "Location and Coverage Analysis of Bike- Sharing Stations in University Campus," Business Systems Research, Sciendo, vol. 9(2), pages 80-95, July.
    4. Patrizia Beraldi & Andrzej Ruszczyński, 2002. "The Probabilistic Set-Covering Problem," Operations Research, INFORMS, vol. 50(6), pages 956-967, December.
    5. Wang, Yiyuan & Pan, Shiwei & Al-Shihabi, Sameh & Zhou, Junping & Yang, Nan & Yin, Minghao, 2021. "An improved configuration checking-based algorithm for the unicost set covering problem," European Journal of Operational Research, Elsevier, vol. 294(2), pages 476-491.
    6. Grossman, Tal & Wool, Avishai, 1997. "Computational experience with approximation algorithms for the set covering problem," European Journal of Operational Research, Elsevier, vol. 101(1), pages 81-92, August.
    7. Ferdinando Pezzella & Enrico Faggioli, 1997. "Solving large set covering problems for crew scheduling," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 5(1), pages 41-59, June.
    8. J. E. Beasley, 1990. "A lagrangian heuristic for set‐covering problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 37(1), pages 151-164, February.
    9. Wanders, Henrico L. T. & Gaalman, Gerard J. C. & Sierksma, Gerard, 2004. "The composition of semi-finished inventories at a solid board plant," European Journal of Operational Research, Elsevier, vol. 155(1), pages 96-111, May.
    10. Olivier Briant & Denis Naddef, 2004. "The Optimal Diversity Management Problem," Operations Research, INFORMS, vol. 52(4), pages 515-526, August.
    11. İbrahim Miraç Eligüzel & Eren Özceylan & Gerhard-Wilhelm Weber, 2023. "Location-allocation analysis of humanitarian distribution plans: a case of United Nations Humanitarian Response Depots," Annals of Operations Research, Springer, vol. 324(1), pages 825-854, May.
    12. Victor Reyes & Ignacio Araya, 2021. "A GRASP-based scheme for the set covering problem," Operational Research, Springer, vol. 21(4), pages 2391-2408, December.
    13. Galvao, Roberto D. & Gonzalo Acosta Espejo, Luis & Boffey, Brian, 2000. "A comparison of Lagrangean and surrogate relaxations for the maximal covering location problem," European Journal of Operational Research, Elsevier, vol. 124(2), pages 377-389, July.
    14. Nguyen, Tri-Dung, 2014. "A fast approximation algorithm for solving the complete set packing problem," European Journal of Operational Research, Elsevier, vol. 237(1), pages 62-70.
    15. Chunyan Liu & Hejiao Huang & Hongwei Du & Xiaohua Jia, 2017. "Optimal RSUs placement with delay bounded message dissemination in vehicular networks," Journal of Combinatorial Optimization, Springer, vol. 33(4), pages 1276-1299, May.
    16. Gianpiero Canessa & Julian A. Gallego & Lewis Ntaimo & Bernardo K. Pagnoncelli, 2019. "An algorithm for binary linear chance-constrained problems using IIS," Computational Optimization and Applications, Springer, vol. 72(3), pages 589-608, April.
    17. Helena Ramalhinho-Lourenço, 2001. "The crew-scheduling module in the GIST system," Economics Working Papers 547, Department of Economics and Business, Universitat Pompeu Fabra.
    18. Larry W. Jacobs & Michael J. Brusco, 1995. "Note: A local‐search heuristic for large set‐covering problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 42(7), pages 1129-1140, October.
    19. Hanif D. Sherali & Seong‐In Kim & Edna L. Parrish, 1991. "Probabilistic partial set covering problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 38(1), pages 41-51, February.
    20. Fabio Colombo & Roberto Cordone & Guglielmo Lulli, 2015. "A variable neighborhood search algorithm for the multimode set covering problem," Journal of Global Optimization, Springer, vol. 63(3), pages 461-480, November.

    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:jmathe:v:11:y:2023:i:20:p:4361-:d:1263859. 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.