IDEAS home Printed from https://ideas.repec.org/p/iim/iimawp/wp00030.html
   My bibliography  Save this paper

Applying Machine Based Decomposition in 2-Machine Flow Shops

Author

Listed:
  • Mukherjee, Saral
  • Chatterjee Ashis K

Abstract

The Shifting Bottleneck (SB) heuristic is among the most successful approximation methods for solving the Job Shop problem. It is essentially a machine based decomposition procedure where a series of One Machine Sequencing Problems (OMSPs) are solved. However, such a procedure has been reported to be highly ineffective for the Flow Shop problems (Jain and Meeran 2002). In particular, we show that for the 2-machine Flow Shop problem, the SB heurisitc will deliver the optimal solution in only a small number of instances. We examine the reason behind the failure of the machine based decomposition method for the Flow Shop. An optimal machine based decomposition procedure is formulated for the 2-machine Flow Shop, the time complexity of which is worse than that of the celebrated Johnsons Rule. The contribution of the present study lies in showing that the same machine based decomposition procedures which are so successful in solving complex Job Shops can also be suitably modified to optimally solve the simpler Flow Shops.

Suggested Citation

  • Mukherjee, Saral & Chatterjee Ashis K, 2002. "Applying Machine Based Decomposition in 2-Machine Flow Shops," IIMA Working Papers WP2002-08-05, Indian Institute of Management Ahmedabad, Research and Publication Department.
    • Handle: RePEc:iim:iimawp:wp00030
    as

    Download full text from publisher

    File URL: https://www.iima.ac.in/sites/default/files/rnpfiles/2002-08-05SaralMukherjee.pdf
    File Function: English Version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carlier, Jacques, 1982. "The one-machine sequencing problem," European Journal of Operational Research, Elsevier, vol. 11(1), pages 42-47, September.
    2. Michael Pinedo & Marcos Singer, 1999. "A shifting bottleneck heuristic for minimizing the total weighted tardiness in a job shop," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(1), pages 1-17, February.
    3. Osman, IH & Potts, CN, 1989. "Simulated annealing for permutation flow-shop scheduling," Omega, Elsevier, vol. 17(6), pages 551-557.
    4. Ramudhin, Amar & Marier, Philippe, 1996. "The generalized Shifting Bottleneck Procedure," European Journal of Operational Research, Elsevier, vol. 93(1), pages 34-48, August.
    5. Joseph Adams & Egon Balas & Daniel Zawack, 1988. "The Shifting Bottleneck Procedure for Job Shop Scheduling," Management Science, INFORMS, vol. 34(3), pages 391-401, March.
    6. Nawaz, Muhammad & Enscore Jr, E Emory & Ham, Inyong, 1983. "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, Elsevier, vol. 11(1), pages 91-95.
    7. J. Carlier & E. Pinson, 1989. "An Algorithm for Solving the Job-Shop Problem," Management Science, INFORMS, vol. 35(2), pages 164-176, February.
    8. Egon Balas & Jan Karel Lenstra & Alkis Vazacopoulos, 1995. "The One-Machine Problem with Delayed Precedence Constraints and its Use in Job Shop Scheduling," Management Science, INFORMS, vol. 41(1), pages 94-109, January.
    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. Mukherjee, Saral & Chatterjee, A.K., 2006. "Applying machine based decomposition in 2-machine flow shops," European Journal of Operational Research, Elsevier, vol. 169(3), pages 723-741, March.
    2. Jain, A. S. & Meeran, S., 1999. "Deterministic job-shop scheduling: Past, present and future," European Journal of Operational Research, Elsevier, vol. 113(2), pages 390-434, March.
    3. Blazewicz, Jacek & Domschke, Wolfgang & Pesch, Erwin, 1996. "The job shop scheduling problem: Conventional and new solution techniques," European Journal of Operational Research, Elsevier, vol. 93(1), pages 1-33, August.
    4. C N Potts & V A Strusevich, 2009. "Fifty years of scheduling: a survey of milestones," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 41-68, May.
    5. Guinet, Alain & Legrand, Marie, 1998. "Reduction of job-shop problems to flow-shop problems with precedence constraints," European Journal of Operational Research, Elsevier, vol. 109(1), pages 96-110, August.
    6. Sheen, Gwo-Ji & Liao, Lu-Wen, 2007. "A branch and bound algorithm for the one-machine scheduling problem with minimum and maximum time lags," European Journal of Operational Research, Elsevier, vol. 181(1), pages 102-116, August.
    7. El-Bouri, A. & Azizi, N. & Zolfaghari, S., 2007. "A comparative study of a new heuristic based on adaptive memory programming and simulated annealing: The case of job shop scheduling," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1894-1910, March.
    8. Da Col, Giacomo & Teppan, Erich C., 2022. "Industrial-size job shop scheduling with constraint programming," Operations Research Perspectives, Elsevier, vol. 9(C).
    9. Egon Balas & Alkis Vazacopoulos, 1998. "Guided Local Search with Shifting Bottleneck for Job Shop Scheduling," Management Science, INFORMS, vol. 44(2), pages 262-275, February.
    10. Ramalhinho Lourenco, Helena, 1996. "Sevast'yanov's algorithm for the flow-shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 91(1), pages 176-189, May.
    11. Ansis Ozolins, 2020. "Bounded dynamic programming algorithm for the job shop problem with sequence dependent setup times," Operational Research, Springer, vol. 20(3), pages 1701-1728, September.
    12. Egon Balas & Giuseppe Lancia & Paolo Serafini & Alkiviadis Vazacopoulos, 1998. "Job Shop Scheduling With Deadlines," Journal of Combinatorial Optimization, Springer, vol. 1(4), pages 329-353, December.
    13. Mascis, Alessandro & Pacciarelli, Dario, 2002. "Job-shop scheduling with blocking and no-wait constraints," European Journal of Operational Research, Elsevier, vol. 143(3), pages 498-517, December.
    14. Pezzella, Ferdinando & Merelli, Emanuela, 2000. "A tabu search method guided by shifting bottleneck for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 120(2), pages 297-310, January.
    15. Francis Sourd & Wim Nuijten, 2000. "Multiple-Machine Lower Bounds for Shop-Scheduling Problems," INFORMS Journal on Computing, INFORMS, vol. 12(4), pages 341-352, November.
    16. Raja Awais Liaqait & Shermeen Hamid & Salman Sagheer Warsi & Azfar Khalid, 2021. "A Critical Analysis of Job Shop Scheduling in Context of Industry 4.0," Sustainability, MDPI, vol. 13(14), pages 1-19, July.
    17. Zijm, W. H. M. & Buitenhek, R., 1996. "Capacity planning and lead time management," International Journal of Production Economics, Elsevier, vol. 46(1), pages 165-179, December.
    18. Braune, R. & Zäpfel, G. & Affenzeller, M., 2012. "An exact approach for single machine subproblems in shifting bottleneck procedures for job shops with total weighted tardiness objective," European Journal of Operational Research, Elsevier, vol. 218(1), pages 76-85.
    19. Marc R. Lambrecht & Philip L. Ivens & Nico J. Vandaele, 1998. "ACLIPS: A Capacity and Lead Time Integrated Procedure for Scheduling," Management Science, INFORMS, vol. 44(11-Part-1), pages 1548-1561, November.
    20. Lourenco, Helena Ramalhinho, 1995. "Job-shop scheduling: Computational study of local search and large-step optimization methods," European Journal of Operational Research, Elsevier, vol. 83(2), pages 347-364, June.

    More about this item

    Statistics

    Access and download statistics

    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:iim:iimawp:wp00030. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/eciimin.html .

    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.