IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v35y2018i3d10.1007_s10878-017-0190-5.html
   My bibliography  Save this article

A randomized competitive group testing procedure

Author

Listed:
  • Guiqing Zhang

    (Xi’an Jiaotong University)

  • Yongxi Cheng

    (Xi’an Jiaotong University
    State Key Lab for Manufacturing Systems Engineering)

  • Yinfeng Xu

    (Xi’an Jiaotong University)

Abstract

In many fault detection problems, we want to identify all defective items from a set of n items using the minimum number of tests. Group testing is for the scenario where each test is on a subset of items, and tells whether the subset contains at least one defective item or not. In practice, the number d of defective items is often unknown in advance. In this paper, we propose a randomized group testing procedure RGT for the scenario where the number d of defectives is unknown in advance, and prove that RGT is competitive. By incorporating numerical results, we obtain improved upper bounds on the expected number of tests performed by RGT, for $$1\le d\le 10^6$$ 1 ≤ d ≤ 10 6 . In particular, for $$1\le d\le 10^6$$ 1 ≤ d ≤ 10 6 and the special case where n is a power of 2, we obtain an upper bound of $$d\log \frac{n}{d}+Cd+O(\log d)$$ d log n d + C d + O ( log d ) with $$C\approx 2.67$$ C ≈ 2.67 on the expected number of tests performed by RGT, which is better than the currently best upper bound in Cheng et al. (INFORMS J Comput 26(4):677–689, 2014). We conjecture that the above improved upper bounds based on numerical results from $$1\le d\le 10^6$$ 1 ≤ d ≤ 10 6 actually hold for all $$d\ge 1$$ d ≥ 1 .

Suggested Citation

  • Guiqing Zhang & Yongxi Cheng & Yinfeng Xu, 2018. "A randomized competitive group testing procedure," Journal of Combinatorial Optimization, Springer, vol. 35(3), pages 667-683, April.
  • Handle: RePEc:spr:jcomop:v:35:y:2018:i:3:d:10.1007_s10878-017-0190-5
    DOI: 10.1007/s10878-017-0190-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-017-0190-5
    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/s10878-017-0190-5?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. Yongxi Cheng & Ding-Zhu Du & Yinfeng Xu, 2014. "A Zig-Zag Approach for Competitive Group Testing," INFORMS Journal on Computing, INFORMS, vol. 26(4), pages 677-689, November.
    2. Lawrence M. Wein & Stefanos A. Zenios, 1996. "Pooled Testing for HIV Screening: Capturing the Dilution Effect," Operations Research, INFORMS, vol. 44(4), pages 543-569, August.
    3. Yongxi Cheng & Yinfeng Xu, 2014. "An efficient FPRAS type group testing procedure to approximate the number of defectives," Journal of Combinatorial Optimization, Springer, vol. 27(2), pages 302-314, February.
    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. Yongxi Cheng & Ding-Zhu Du & Feifeng Zheng, 2015. "A new strongly competitive group testing algorithm with small sequentiality," Annals of Operations Research, Springer, vol. 229(1), pages 265-286, June.
    2. Bar-Lev, S.K. & Parlar, M. & Perry, D. & Stadje, W. & van der Duyn Schouten, F.A., 2007. "Applications of bulk queues to group testing models with incomplete identification," Other publications TiSEM 0b1bfa5e-c1e6-43ec-9684-1, Tilburg University, School of Economics and Management.
    3. Hae-Young Kim & Michael G. Hudgens & Jonathan M. Dreyfuss & Daniel J. Westreich & Christopher D. Pilcher, 2007. "Comparison of Group Testing Algorithms for Case Identification in the Presence of Test Error," Biometrics, The International Biometric Society, vol. 63(4), pages 1152-1163, December.
    4. Hrayer Aprahamian & Douglas R. Bish & Ebru K. Bish, 2020. "Optimal Group Testing: Structural Properties and Robust Solutions, with Application to Public Health Screening," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 895-911, October.
    5. Sarah Kok & Alexander Rutherford & Reka Gustafson & Rolando Barrios & Julio Montaner & Krisztina Vasarhelyi, 2015. "Optimizing an HIV testing program using a system dynamics model of the continuum of care," Health Care Management Science, Springer, vol. 18(3), pages 334-362, September.
    6. Hrayer Aprahamian & Douglas R. Bish & Ebru K. Bish, 2019. "Optimal Risk-Based Group Testing," Management Science, INFORMS, vol. 65(9), pages 4365-4384, September.
    7. Shaul K. Bar-Lev & Wolfgang Stadje & Frank A. van der Duyn Schouten, 2004. "Optimal Group Testing with Processing Times and Incomplete Identification," Methodology and Computing in Applied Probability, Springer, vol. 6(1), pages 55-72, March.
    8. Shaul K. Bar‐Lev & Onno Boxma & Andreas Löpker & Wolfgang Stadje & Frank A. Van der Duyn Schouten, 2012. "Group testing procedures with quantitative features and incomplete identification," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(1), pages 39-51, February.
    9. Gustavo Quinderé Saraiva, 2023. "Pool testing with dilution effects and heterogeneous priors," Health Care Management Science, Springer, vol. 26(4), pages 651-672, December.
    10. Bar-Lev, Shaul K. & Boxma, Onno & Kleiner, Igor & Perry, David & Stadje, Wolfgang, 2017. "Recycled incomplete identification procedures for blood screening," European Journal of Operational Research, Elsevier, vol. 259(1), pages 330-343.
    11. Pritha Guha, 2022. "Application of Pooled Testing Methodologies in Tackling the COVID-19 Pandemic," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 47(1), pages 7-21, February.
    12. Bar-Lev, S.K. & Stadje, W. & van der Duyn Schouten, F.A., 2002. "Group Testing Models with Processing Times and Incomplete Identification," Discussion Paper 2002-75, Tilburg University, Center for Economic Research.
    13. Shaul K. Bar-Lev & Hans Blanc & Onno Boxma & Guido Janssen & David Perry, 2013. "Tandem Queues with Impatient Customers for Blood Screening Procedures," Methodology and Computing in Applied Probability, Springer, vol. 15(2), pages 423-451, June.
    14. Yongxi Cheng & Jue Guo & Feifeng Zheng, 2015. "A new randomized algorithm for group testing with unknown number of defective items," Journal of Combinatorial Optimization, Springer, vol. 30(1), pages 150-159, July.
    15. Bar-Lev, S.K. & Stadje, W. & van der Duyn Schouten, F.A., 2002. "Hypergeometric Group Testing with Incomplete Information," Other publications TiSEM bbeda767-e037-4441-a6d4-6, Tilburg University, School of Economics and Management.
    16. Yongxi Cheng & Yinfeng Xu, 2014. "An efficient FPRAS type group testing procedure to approximate the number of defectives," Journal of Combinatorial Optimization, Springer, vol. 27(2), pages 302-314, February.
    17. Tarun Jain & Bijendra Nath Jain, 2021. "Infection Testing at Scale: An Examination of Pooled Testing Diagnostics," Vikalpa: The Journal for Decision Makers, , vol. 46(1), pages 13-26, March.
    18. Claeys, Dieter & Walraevens, Joris & Laevens, Koenraad & Bruneel, Herwig, 2010. "A queueing model for general group screening policies and dynamic item arrivals," European Journal of Operational Research, Elsevier, vol. 207(2), pages 827-835, December.
    19. Hrayer Aprahamian & Hadi El-Amine, 2022. "Optimal Screening of Populations with Heterogeneous Risk Profiles Under the Availability of Multiple Tests," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 150-164, January.
    20. Nguyen, Ngoc T. & Bish, Ebru K. & Bish, Douglas R., 2021. "Optimal pooled testing design for prevalence estimation under resource constraints," Omega, Elsevier, vol. 105(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:spr:jcomop:v:35:y:2018:i:3:d:10.1007_s10878-017-0190-5. 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.