IDEAS home Printed from https://ideas.repec.org/a/spr/aqjoor/v19y2021i4d10.1007_s10288-020-00463-w.html
   My bibliography  Save this article

A binary search algorithm for the general coupled task scheduling problem

Author

Listed:
  • Mostafa Khatami

    (University of Technology Sydney)

  • Amir Salehipour

    (University of Technology Sydney)

Abstract

The coupled task scheduling problem aims to schedule a set of jobs, each with at least two tasks and there is an exact delay period between two consecutive tasks, on a set of machines to optimize a performance criterion. We study the problem of scheduling a set of coupled jobs to be processed on a single machine with the objective of minimizing the makespan, which is known to be strongly NP-hard. We obtain competitive lower bounds for the problem through different procedures, including solving 0-1 knapsack problems. We obtain an upper bound by applying a heuristic algorithm. We then propose a binary search heuristic algorithm for the coupled task scheduling problem. We perform extensive computational experiments and show that the proposed method is able to obtain quality solutions. The results also indicate that the proposed solution method outperforms the standard exact solver Gurobi.

Suggested Citation

  • Mostafa Khatami & Amir Salehipour, 2021. "A binary search algorithm for the general coupled task scheduling problem," 4OR, Springer, vol. 19(4), pages 593-611, December.
    • Handle: RePEc:spr:aqjoor:v:19:y:2021:i:4:d:10.1007_s10288-020-00463-w
    DOI: 10.1007/s10288-020-00463-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10288-020-00463-w
    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/s10288-020-00463-w?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. Eduardo Pérez & Lewis Ntaimo & César Malavé & Carla Bailey & Peter McCormack, 2013. "Stochastic online appointment scheduling of multi-step sequential procedures in nuclear medicine," Health Care Management Science, Springer, vol. 16(4), pages 281-299, December.
    2. József Békési & Gábor Galambos & Michael Jung & Marcus Oswald & Gerhard Reinelt, 2014. "A branch-and-bound algorithm for the coupled task problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 80(1), pages 47-81, August.
    3. Paulo M. França & Michel Gendreau & Gilbert Laporte & Felipe M. Müller, 1995. "The m -Traveling Salesman Problem with Minmax Objective," Transportation Science, INFORMS, vol. 29(3), pages 267-275, August.
    4. Diarmuid Grimes & Emmanuel Hebrard, 2015. "Solving Variants of the Job Shop Scheduling Problem Through Conflict-Directed Search," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 268-284, May.
    5. Khatami, Mostafa & Salehipour, Amir & Cheng, T.C.E., 2020. "Coupled task scheduling with exact delays: Literature review and models," European Journal of Operational Research, Elsevier, vol. 282(1), pages 19-39.
    6. Carlier, J. & Neron, E., 2003. "On linear lower bounds for the resource constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 149(2), pages 314-324, September.
    7. Roy D. Shapiro, 1980. "Scheduling coupled tasks," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 27(3), pages 489-498, September.
    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. David Fischer & Péter Györgyi, 2023. "Approximation algorithms for coupled task scheduling minimizing the sum of completion times," Annals of Operations Research, Springer, vol. 328(2), pages 1387-1408, September.

    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. Mostafa Khatami & Amir Salehipour, 2021. "Coupled task scheduling with time-dependent processing times," Journal of Scheduling, Springer, vol. 24(2), pages 223-236, April.
    2. David Fischer & Péter Györgyi, 2023. "Approximation algorithms for coupled task scheduling minimizing the sum of completion times," Annals of Operations Research, Springer, vol. 328(2), pages 1387-1408, September.
    3. Bo Chen & Xiandong Zhang, 2021. "Scheduling coupled tasks with exact delays for minimum total job completion time," Journal of Scheduling, Springer, vol. 24(2), pages 209-221, April.
    4. Khatami, Mostafa & Salehipour, Amir & Cheng, T.C.E., 2020. "Coupled task scheduling with exact delays: Literature review and models," European Journal of Operational Research, Elsevier, vol. 282(1), pages 19-39.
    5. Michelle Alvarado & Lewis Ntaimo, 2018. "Chemotherapy appointment scheduling under uncertainty using mean-risk stochastic integer programming," Health Care Management Science, Springer, vol. 21(1), pages 87-104, March.
    6. Moukrim, Aziz & Quilliot, Alain & Toussaint, Hélène, 2015. "An effective branch-and-price algorithm for the Preemptive Resource Constrained Project Scheduling Problem based on minimal Interval Order Enumeration," European Journal of Operational Research, Elsevier, vol. 244(2), pages 360-368.
    7. Dogru, Ali K. & Melouk, Sharif H., 2019. "Adaptive appointment scheduling for patient-centered medical homes," Omega, Elsevier, vol. 85(C), pages 166-181.
    8. Bürgy, Reinhard & Bülbül, Kerem, 2018. "The job shop scheduling problem with convex costs," European Journal of Operational Research, Elsevier, vol. 268(1), pages 82-100.
    9. Zhu, Xuedong & Son, Junbo & Zhang, Xi & Wu, Jianguo, 2023. "Constraint programming and logic-based Benders decomposition for the integrated process planning and scheduling problem," Omega, Elsevier, vol. 117(C).
    10. Arkhipov, Dmitry & Battaïa, Olga & Lazarev, Alexander, 2019. "An efficient pseudo-polynomial algorithm for finding a lower bound on the makespan for the Resource Constrained Project Scheduling Problem," European Journal of Operational Research, Elsevier, vol. 275(1), pages 35-44.
    11. Carlier, Jacques & Neron, Emmanuel, 2007. "Computing redundant resources for the resource constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1452-1463, February.
    12. Ann Melissa Campbell & Dieter Vandenbussche & William Hermann, 2008. "Routing for Relief Efforts," Transportation Science, INFORMS, vol. 42(2), pages 127-145, May.
    13. Andrés Miniguano-Trujillo & Fernanda Salazar & Ramiro Torres & Patricio Arias & Koraima Sotomayor, 2021. "An integer programming model to assign patients based on mental health impact for tele-psychotherapy intervention during the Covid–19 emergency," Health Care Management Science, Springer, vol. 24(2), pages 286-304, June.
    14. Thierry Garaix & Salim Rostami & Xiaolan Xie, 2020. "Daily outpatient chemotherapy appointment scheduling with random deferrals," Flexible Services and Manufacturing Journal, Springer, vol. 32(1), pages 129-153, March.
    15. Eduardo Pérez & David P. Dzubay, 2021. "A scheduling-based methodology for improving patient perceptions of quality of care in intensive care units," Health Care Management Science, Springer, vol. 24(1), pages 203-215, March.
    16. Eduardo Pérez, 2022. "An Appointment Planning Algorithm for Reducing Patient Check-In Waiting Times in Multispecialty Outpatient Clinics," SN Operations Research Forum, Springer, vol. 3(3), pages 1-22, September.
    17. Xuanzhu Fan & Jiafu Tang & Chongjun Yan, 2020. "Appointment scheduling optimization with two stages diagnosis for clinic outpatient," Computational Statistics, Springer, vol. 35(2), pages 469-490, June.
    18. Dina Bentayeb & Nadia Lahrichi & Louis-Martin Rousseau, 2023. "On integrating patient appointment grids and technologist schedules in a radiology center," Health Care Management Science, Springer, vol. 26(1), pages 62-78, March.
    19. Sévérine Fetgo Betmbe & Clémentin Tayou Djamegni, 2022. "Horizontally Elastic Edge-Finder Algorithm for Cumulative Resource Constraint Revisited," SN Operations Research Forum, Springer, vol. 3(4), pages 1-32, December.
    20. Nadjat Meziani & Ammar Oulamara & Mourad Boudhar, 2019. "Two-machine flowshop scheduling problem with coupled-operations," Annals of Operations Research, Springer, vol. 275(2), pages 511-530, April.

    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:aqjoor:v:19:y:2021:i:4:d:10.1007_s10288-020-00463-w. 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.