IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v55y2004i5d10.1057_palgrave.jors.2601716.html
   My bibliography  Save this article

Multiprocessor task scheduling in multistage hybrid flow-shops: a genetic algorithm approach

Author

Listed:
  • F Sivrikaya şerifoğlu

    (Abant Izzet Baysal University)

  • G Ulusoy

    (Sabanci University)

Abstract

This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment. The objective is to minimize the make-span, that is, the completion time of all the tasks in the last stage. This problem is of practical interest in the textile and process industries. A genetic algorithm (GA) is developed to solve the problem. The GA is tested against a lower bound from the literature as well as against heuristic rules on a test bed comprising 400 problems with up to 100 jobs, 10 stages, and with up to five processors on each stage. For small problems, solutions found by the GA are compared to optimal solutions, which are obtained by total enumeration. For larger problems, optimum solutions are estimated by a statistical prediction technique. Computational results show that the GA is both effective and efficient for the current problem. Test problems are provided in a web site at www.benchmark.ibu.edu.tr/mpt-hfsp .

Suggested Citation

  • F Sivrikaya şerifoğlu & G Ulusoy, 2004. "Multiprocessor task scheduling in multistage hybrid flow-shops: a genetic algorithm approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(5), pages 504-512, May.
    • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:5:d:10.1057_palgrave.jors.2601716
    DOI: 10.1057/palgrave.jors.2601716
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palgrave.jors.2601716
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/palgrave.jors.2601716?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. Valerie Botta-Genoulaz, 2000. "Hybrid flow shop scheduling with precedence constraints and time lags to minimize maximum lateness," Post-Print hal-00398647, HAL.
    2. Hoogeveen, J. A. & Lenstra, J. K. & Veltman, B., 1996. "Preemptive scheduling in a two-stage multiprocessor flow shop is NP-hard," European Journal of Operational Research, Elsevier, vol. 89(1), pages 172-175, February.
    3. Drozdowski, Maciej, 1996. "Scheduling multiprocessor tasks -- An overview," European Journal of Operational Research, Elsevier, vol. 94(2), pages 215-230, October.
    4. Portmann, M. -C. & Vignier, A. & Dardilhac, D. & Dezalay, D., 1998. "Branch and bound crossed with GA to solve hybrid flowshops," European Journal of Operational Research, Elsevier, vol. 107(2), pages 389-400, June.
    5. Botta-Genoulaz, Valerie, 2000. "Hybrid flow shop scheduling with precedence constraints and time lags to minimize maximum lateness," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 101-111, March.
    6. Jianer Chen & Chung‐Yee Lee, 1999. "General multiprocessor task scheduling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(1), pages 57-74, February.
    7. Moursli, O. & Pochet, Y., 2000. "A branch-and-bound algorithm for the hybrid flowshop," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 113-125, March.
    8. Brucker, Peter & Kramer, Andreas, 1996. "Polynomial algorithms for resource-constrained and multiprocessor task scheduling problems," European Journal of Operational Research, Elsevier, vol. 90(2), pages 214-226, April.
    9. Negenman, Ebbe G., 2001. "Local search algorithms for the multiprocessor flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 128(1), pages 147-158, January.
    10. Chung-Yee Lee & Lei Lei & Michael Pinedo, 1997. "Current trends in deterministic scheduling," Annals of Operations Research, Springer, vol. 70(0), pages 1-41, April.
    11. Dessouky, Maged M. & Dessouky, Mohamed I. & Verma, Sushil K., 1998. "Flowshop scheduling with identical jobs and uniform parallel machines," European Journal of Operational Research, Elsevier, vol. 109(3), pages 620-631, September.
    12. Santos, D. L. & Hunsucker, J. L. & Deal, D. E., 1995. "Global lower bounds for flow shops with multiple processors," European Journal of Operational Research, Elsevier, vol. 80(1), pages 112-120, January.
    13. Oguz, C. & Fikret Ercan, M. & Edwin Cheng, T. C. & Fung, Y. F., 2003. "Heuristic algorithms for multiprocessor task scheduling in a two-stage hybrid flow-shop," European Journal of Operational Research, Elsevier, vol. 149(2), pages 390-403, 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. Zhen Song & Håkan Schunnesson & Mikael Rinne & John Sturgul, 2015. "Intelligent Scheduling for Underground Mobile Mining Equipment," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-21, June.
    2. Quadt, Daniel & Kuhn, Heinrich, 2007. "A taxonomy of flexible flow line scheduling procedures," European Journal of Operational Research, Elsevier, vol. 178(3), pages 686-698, May.
    3. Carlos Paternina-Arboleda & Jairo Montoya-Torres & Milton Acero-Dominguez & Maria Herrera-Hernandez, 2008. "Scheduling jobs on a k-stage flexible flow-shop," Annals of Operations Research, Springer, vol. 164(1), pages 29-40, November.
    4. Cha, Young-Ho & Kim, Yeong-Dae, 2010. "Fire scheduling for planned artillery attack operations under time-dependent destruction probabilities," Omega, Elsevier, vol. 38(5), pages 383-392, October.
    5. Ruiz, Rubén & Vázquez-Rodríguez, José Antonio, 2010. "The hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 1-18, August.
    6. K-C Ying, 2009. "An iterated greedy heuristic for multistage hybrid flowshop scheduling problems with multiprocessor tasks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(6), pages 810-817, June.
    7. Chou, Fuh-Der, 2013. "Particle swarm optimization with cocktail decoding method for hybrid flow shop scheduling problems with multiprocessor tasks," International Journal of Production Economics, Elsevier, vol. 141(1), pages 137-145.

    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. Ruiz, Rubén & Vázquez-Rodríguez, José Antonio, 2010. "The hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 1-18, August.
    2. Carlos Paternina-Arboleda & Jairo Montoya-Torres & Milton Acero-Dominguez & Maria Herrera-Hernandez, 2008. "Scheduling jobs on a k-stage flexible flow-shop," Annals of Operations Research, Springer, vol. 164(1), pages 29-40, November.
    3. Quadt, Daniel & Kuhn, Heinrich, 2007. "A taxonomy of flexible flow line scheduling procedures," European Journal of Operational Research, Elsevier, vol. 178(3), pages 686-698, May.
    4. Bertel, S. & Billaut, J. -C., 2004. "A genetic algorithm for an industrial multiprocessor flow shop scheduling problem with recirculation," European Journal of Operational Research, Elsevier, vol. 159(3), pages 651-662, December.
    5. Wu, Lingxiao & Wang, Shuaian, 2018. "Exact and heuristic methods to solve the parallel machine scheduling problem with multi-processor tasks," International Journal of Production Economics, Elsevier, vol. 201(C), pages 26-40.
    6. Marco Schulze & Julia Rieck & Cinna Seifi & Jürgen Zimmermann, 2016. "Machine scheduling in underground mining: an application in the potash industry," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(2), pages 365-403, March.
    7. Mohamed Haouari & Lotfi Hidri & Anis Gharbi, 2006. "Optimal Scheduling of a Two-stage Hybrid Flow Shop," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 64(1), pages 107-124, August.
    8. Kis, Tamas & Pesch, Erwin, 2005. "A review of exact solution methods for the non-preemptive multiprocessor flowshop problem," European Journal of Operational Research, Elsevier, vol. 164(3), pages 592-608, August.
    9. Oguz, Ceyda & Zinder, Yakov & Ha Do, Van & Janiak, Adam & Lichtenstein, Maciej, 2004. "Hybrid flow-shop scheduling problems with multiprocessor task systems," European Journal of Operational Research, Elsevier, vol. 152(1), pages 115-131, January.
    10. Janiak, Adam & Kozan, Erhan & Lichtenstein, Maciej & Oguz, Ceyda, 2007. "Metaheuristic approaches to the hybrid flow shop scheduling problem with a cost-related criterion," International Journal of Production Economics, Elsevier, vol. 105(2), pages 407-424, February.
    11. Ferreira, Cristiane & Figueira, Gonçalo & Amorim, Pedro, 2021. "Scheduling Human-Robot Teams in collaborative working cells," International Journal of Production Economics, Elsevier, vol. 235(C).
    12. Chen, Lu & Bostel, Nathalie & Dejax, Pierre & Cai, Jianguo & Xi, Lifeng, 2007. "A tabu search algorithm for the integrated scheduling problem of container handling systems in a maritime terminal," European Journal of Operational Research, Elsevier, vol. 181(1), pages 40-58, August.
    13. Oguz, C. & Fikret Ercan, M. & Edwin Cheng, T. C. & Fung, Y. F., 2003. "Heuristic algorithms for multiprocessor task scheduling in a two-stage hybrid flow-shop," European Journal of Operational Research, Elsevier, vol. 149(2), pages 390-403, September.
    14. Chou, Fuh-Der, 2013. "Particle swarm optimization with cocktail decoding method for hybrid flow shop scheduling problems with multiprocessor tasks," International Journal of Production Economics, Elsevier, vol. 141(1), pages 137-145.
    15. Chen, Yin-Yann & Cheng, Chen-Yang & Wang, Li-Chih & Chen, Tzu-Li, 2013. "A hybrid approach based on the variable neighborhood search and particle swarm optimization for parallel machine scheduling problems—A case study for solar cell industry," International Journal of Production Economics, Elsevier, vol. 141(1), pages 66-78.
    16. Jingui Huang & Jianer Chen & Songqiao Chen & Jianxin Wang, 2007. "A simple linear time approximation algorithm for multi-processor job scheduling on four processors," Journal of Combinatorial Optimization, Springer, vol. 13(1), pages 33-45, January.
    17. Allahverdi, Ali & Ng, C.T. & Cheng, T.C.E. & Kovalyov, Mikhail Y., 2008. "A survey of scheduling problems with setup times or costs," European Journal of Operational Research, Elsevier, vol. 187(3), pages 985-1032, June.
    18. Theodor Freiheit & Wei Li, 2017. "The effect of work content imbalance and its interaction with scheduling method on sequential flow line performance," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 2791-2805, May.
    19. Ann Vandevelde & Han Hoogeveen & Cor Hurkens & Jan Karel Lenstra, 2005. "Lower Bounds for the Head-Body-Tail Problem on Parallel Machines: A Computational Study of the Multiprocessor Flow Shop," INFORMS Journal on Computing, INFORMS, vol. 17(3), pages 305-320, August.
    20. Weng, Wei & Fujimura, Shigeru, 2012. "Control methods for dynamic time-based manufacturing under customized product lead times," European Journal of Operational Research, Elsevier, vol. 218(1), pages 86-96.

    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:pal:jorsoc:v:55:y:2004:i:5:d:10.1057_palgrave.jors.2601716. 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.palgrave-journals.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.