IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v28y2017i8d10.1007_s10845-015-1078-9.html
   My bibliography  Save this article

Embedding ant system in genetic algorithm for re-entrant hybrid flow shop scheduling problems with time window constraints

Author

Listed:
  • Chettha Chamnanlor

    (Khon Kaen University)

  • Kanchana Sethanan

    (Khon Kaen University)

  • Mitsuo Gen

    (Tokyo University of Science
    Fuzzy Logic Systems Institute)

  • Chen-Fu Chien

    (National Tsing Hua University)

Abstract

This paper focuses on minimizing the makespan for a reentrant hybrid flow shop scheduling problem with time window constraints (RHFSTW), which is often found in manufacturing systems producing the slider part of hard-disk drive products, in which production needs to be monitored to ensure high quality. For this reason, production time control is required from the starting-time-window stage to the ending-time-window stage. Because of the complexity of the RHFSTW problem, in this paper, genetic algorithm hybridized ant colony optimization (GACO) is proposed to be used as a support tool for scheduling. The results show that the GACO can solve problems optimally with reasonable computational effort.

Suggested Citation

  • Chettha Chamnanlor & Kanchana Sethanan & Mitsuo Gen & Chen-Fu Chien, 2017. "Embedding ant system in genetic algorithm for re-entrant hybrid flow shop scheduling problems with time window constraints," Journal of Intelligent Manufacturing, Springer, vol. 28(8), pages 1915-1931, December.
    • Handle: RePEc:spr:joinma:v:28:y:2017:i:8:d:10.1007_s10845-015-1078-9
    DOI: 10.1007/s10845-015-1078-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-015-1078-9
    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/s10845-015-1078-9?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. Ruiz, Ruben & Maroto, Concepcion & Alcaraz, Javier, 2005. "Solving the flowshop scheduling problem with sequence dependent setup times using advanced metaheuristics," European Journal of Operational Research, Elsevier, vol. 165(1), pages 34-54, August.
    2. Haipeng Zhang & Mitsuo Gen, 2009. "A parallel hybrid ant colony optimisation approach for job-shop scheduling problem," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 16(1/2), pages 22-41.
    3. Dugardin, Frédéric & Yalaoui, Farouk & Amodeo, Lionel, 2010. "New multi-objective method to solve reentrant hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 203(1), pages 22-31, May.
    4. JC-H Pan & J-S Chen, 2003. "Minimizing makespan in re-entrant permutation flow-shops," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(6), pages 642-653, June.
    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. Fan Yang & Roel Leus, 2021. "Scheduling hybrid flow shops with time windows," Journal of Heuristics, Springer, vol. 27(1), pages 133-158, April.
    2. Konstantinos S. Boulas & Georgios D. Dounias & Chrissoleon T. Papadopoulos, 2023. "A hybrid evolutionary algorithm approach for estimating the throughput of short reliable approximately balanced production lines," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 823-852, February.
    3. Zheng Xiao & Zhenan Wang & Deng Liu & Hui Wang, 2022. "A path planning algorithm for PCB surface quality automatic inspection," Journal of Intelligent Manufacturing, Springer, vol. 33(6), pages 1829-1841, August.
    4. Mohamed Kriouich & Hicham Sarir, 2024. "Artificial Intelligence Application in Production Scheduling Problem Systematic Literature Review: Bibliometric Analysis, Research Trend, and Knowledge Taxonomy," SN Operations Research Forum, Springer, vol. 5(2), pages 1-24, June.
    5. Maedeh Fasihi & Reza Tavakkoli-Moghaddam & Fariborz Jolai, 2023. "A bi-objective re-entrant permutation flow shop scheduling problem: minimizing the makespan and maximum tardiness," Operational Research, Springer, vol. 23(2), pages 1-41, June.

    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. 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. Bozorgirad, Mir Abbas & Logendran, Rasaratnam, 2013. "Bi-criteria group scheduling in hybrid flowshops," International Journal of Production Economics, Elsevier, vol. 145(2), pages 599-612.
    3. Jianxin Fang & Brenda Cheang & Andrew Lim, 2023. "Problems and Solution Methods of Machine Scheduling in Semiconductor Manufacturing Operations: A Survey," Sustainability, MDPI, vol. 15(17), pages 1-44, August.
    4. Shahvari, Omid & Logendran, Rasaratnam, 2016. "Hybrid flow shop batching and scheduling with a bi-criteria objective," International Journal of Production Economics, Elsevier, vol. 179(C), pages 239-258.
    5. Mansouri, S. Afshin & Aktas, Emel & Besikci, Umut, 2016. "Green scheduling of a two-machine flowshop: Trade-off between makespan and energy consumption," European Journal of Operational Research, Elsevier, vol. 248(3), pages 772-788.
    6. Ruiz, Ruben & Stutzle, Thomas, 2007. "A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2033-2049, March.
    7. S. M. Mousavi & I. Mahdavi & J. Rezaeian & M. Zandieh, 2018. "An efficient bi-objective algorithm to solve re-entrant hybrid flow shop scheduling with learning effect and setup times," Operational Research, Springer, vol. 18(1), pages 123-158, April.
    8. Bahman Naderi & Rubén Ruiz & Vahid Roshanaei, 2023. "Mixed-Integer Programming vs. Constraint Programming for Shop Scheduling Problems: New Results and Outlook," INFORMS Journal on Computing, INFORMS, vol. 35(4), pages 817-843, July.
    9. V. Anjana & R. Sridharan & P. N. Ram Kumar, 2020. "Metaheuristics for solving a multi-objective flow shop scheduling problem with sequence-dependent setup times," Journal of Scheduling, Springer, vol. 23(1), pages 49-69, February.
    10. S Afshin Mansouri & Emel Aktas, 2016. "Minimizing energy consumption and makespan in a two-machine flowshop scheduling problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(11), pages 1382-1394, November.
    11. F T Tseng & J N D Gupta & E F Stafford, 2006. "A penalty-based heuristic algorithm for the permutation flowshop scheduling problem with sequence-dependent set-up times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 541-551, May.
    12. 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.
    13. Wieslaw Kubiak & Yanling Feng & Guo Li & Suresh P. Sethi & Chelliah Sriskandarajah, 2020. "Efficient algorithms for flexible job shop scheduling with parallel machines," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(4), pages 272-288, June.
    14. Maedeh Fasihi & Reza Tavakkoli-Moghaddam & Fariborz Jolai, 2023. "A bi-objective re-entrant permutation flow shop scheduling problem: minimizing the makespan and maximum tardiness," Operational Research, Springer, vol. 23(2), pages 1-41, June.
    15. Simge Yelkenci Kose & Ozcan Kilincci, 2020. "A multi-objective hybrid evolutionary approach for buffer allocation in open serial production lines," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 33-51, January.
    16. Ruiz, Ruben & Maroto, Concepcion, 2006. "A genetic algorithm for hybrid flowshops with sequence dependent setup times and machine eligibility," European Journal of Operational Research, Elsevier, vol. 169(3), pages 781-800, March.
    17. Yunhe Wang & Xiangtao Li & Zhiqiang Ma, 2017. "A Hybrid Local Search Algorithm for the Sequence Dependent Setup Times Flowshop Scheduling Problem with Makespan Criterion," Sustainability, MDPI, vol. 9(12), pages 1-35, December.
    18. Nadia Babou & Djamal Rebaine & Mourad Boudhar, 2024. "Solving the two-machine open shop problem with a single server with respect to the makespan," Annals of Operations Research, Springer, vol. 338(2), pages 857-877, July.
    19. Karsu, Özlem & Morton, Alec, 2015. "Inequity averse optimization in operational research," European Journal of Operational Research, Elsevier, vol. 245(2), pages 343-359.
    20. Wenlin Yuan & Xueyan Yu & Chengguo Su & Denghua Yan & Zening Wu, 2020. "A Multi-Timescale Integrated Operation Model for Balancing Power Generation, Ecology, and Water Supply of Reservoir Operation," Energies, MDPI, vol. 14(1), pages 1-21, December.

    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:joinma:v:28:y:2017:i:8:d:10.1007_s10845-015-1078-9. 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.