IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v13y2022i3d10.1007_s13198-021-01411-5.html
   My bibliography  Save this article

Optimization of production scheduling in two stage Flow Shop Scheduling problem with m equipotential machines at first stage

Author

Listed:
  • Deepak Gupta

    (Maharishi Markandeshwar (Deemed To Be University))

  • Sonia Goel

    (Maharishi Markandeshwar (Deemed To Be University))

  • Neeraj Mangla

    (Maharishi Markandeshwar (Deemed To Be University))

Abstract

Scheduling jobs on equipotential machines is an activity that is very much a part of industrial scheduling. This research reports a methodology for minimizing the make span and operating cost of machineries in flow shop scheduling problem with m-equipotential machineries at first stage in addition single machine at second stage. In our research, we develop an algorithm for finding the optimal schedule for two stage flow shop scheduling problem using branch and bound technique. Modified distribution method is applied to find the optimum allocation of processing time of jobs to equipotential machines. The procedure helps the manager to reduce the time of manufacturing and overall production cost.

Suggested Citation

  • Deepak Gupta & Sonia Goel & Neeraj Mangla, 2022. "Optimization of production scheduling in two stage Flow Shop Scheduling problem with m equipotential machines at first stage," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 1162-1169, June.
  • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:3:d:10.1007_s13198-021-01411-5
    DOI: 10.1007/s13198-021-01411-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-021-01411-5
    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/s13198-021-01411-5?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. Shijin Wang & Ming Liu & Chengbin Chu, 2015. "A branch-and-bound algorithm for two-stage no-wait hybrid flow-shop scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 53(4), pages 1143-1167, February.
    2. Kewal Krishan Nailwal & Deepak Gupta & Kawal Jeet & Sameer Sharma, 2019. "An improvement heuristic for permutation flow shop scheduling," International Journal of Process Management and Benchmarking, Inderscience Enterprises Ltd, vol. 9(1), pages 124-148.
    3. Jabrane Belabid & Said Aqil & Karam Allali, 2020. "Solving Permutation Flow Shop Scheduling Problem with Sequence-Independent Setup Time," Journal of Applied Mathematics, Hindawi, vol. 2020, pages 1-11, January.
    4. G. M. Komaki & Shaya Sheikh & Behnam Malakooti, 2019. "Flow shop scheduling problems with assembly operations: a review and new trends," International Journal of Production Research, Taylor & Francis Journals, vol. 57(10), pages 2926-2955, May.
    5. Zeynep Adak & Mahmure Övül Arıoğlu Akan & Serol Bulkan, 2020. "Multiprocessor open shop problem: literature review and future directions," Journal of Combinatorial Optimization, Springer, vol. 40(2), pages 547-569, August.
    6. S. M. Johnson, 1954. "Optimal two‐ and three‐stage production schedules with setup times included," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 1(1), pages 61-68, March.
    7. G. B. McMahon & P. G. Burton, 1967. "Flow-Shop Scheduling with the Branch-and-Bound Method," Operations Research, INFORMS, vol. 15(3), pages 473-481, June.
    8. Gmys, Jan & Mezmaz, Mohand & Melab, Nouredine & Tuyttens, Daniel, 2020. "A computationally efficient Branch-and-Bound algorithm for the permutation flow-shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 284(3), pages 814-833.
    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. Brammer, Janis & Lutz, Bernhard & Neumann, Dirk, 2022. "Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning," European Journal of Operational Research, Elsevier, vol. 299(1), pages 75-86.
    2. Jan Gmys, 2022. "Exactly Solving Hard Permutation Flowshop Scheduling Problems on Peta-Scale GPU-Accelerated Supercomputers," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2502-2522, September.
    3. Olivier Ploton & Vincent T’kindt, 2023. "Moderate worst-case complexity bounds for the permutation flowshop scheduling problem using Inclusion–Exclusion," Journal of Scheduling, Springer, vol. 26(2), pages 137-145, April.
    4. Gmys, Jan & Mezmaz, Mohand & Melab, Nouredine & Tuyttens, Daniel, 2020. "A computationally efficient Branch-and-Bound algorithm for the permutation flow-shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 284(3), pages 814-833.
    5. Sündüz Dağ, 2013. "An Application On Flowshop Scheduling," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 1(1), pages 47-56, December.
    6. Wlodzimierz Szwarc & Jatinder N. D. Gupta, 1987. "A flow‐shop problem with sequence‐dependent additive setup times," Naval Research Logistics (NRL), John Wiley & Sons, vol. 34(5), pages 619-627, October.
    7. Liqi Zhang & Lingfa Lu & Shisheng Li, 2016. "New results on two-machine flow-shop scheduling with rejection," Journal of Combinatorial Optimization, Springer, vol. 31(4), pages 1493-1504, May.
    8. Ganesan, Viswanath Kumar & Sivakumar, Appa Iyer, 2006. "Scheduling in static jobshops for minimizing mean flowtime subject to minimum total deviation of job completion times," International Journal of Production Economics, Elsevier, vol. 103(2), pages 633-647, October.
    9. Niloy J. Mukherjee & Subhash C. Sarin & Daniel A. Neira, 2023. "Lot streaming for a two-stage assembly system in the presence of handling costs," Journal of Scheduling, Springer, vol. 26(4), pages 335-351, August.
    10. Vincent T’kindt & Federico Della Croce & Mathieu Liedloff, 2022. "Moderate exponential-time algorithms for scheduling problems," 4OR, Springer, vol. 20(4), pages 533-566, December.
    11. 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.
    12. Weiwei Cui & Biao Lu, 2020. "A Bi-Objective Approach to Minimize Makespan and Energy Consumption in Flow Shops with Peak Demand Constraint," Sustainability, MDPI, vol. 12(10), pages 1-22, May.
    13. Vineet Jain & Tilak Raj, 2018. "An adaptive neuro-fuzzy inference system for makespan estimation of flexible manufacturing system assembly shop: a case study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(6), pages 1302-1314, December.
    14. Yong Wang & Yuting Wang & Yuyan Han, 2023. "A Variant Iterated Greedy Algorithm Integrating Multiple Decoding Rules for Hybrid Blocking Flow Shop Scheduling Problem," Mathematics, MDPI, vol. 11(11), pages 1-25, May.
    15. Golpîra, Hêriş, 2020. "Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach," Energy, Elsevier, vol. 209(C).
    16. Alexander Grigoriev & Martijn Holthuijsen & Joris van de Klundert, 2005. "Basic scheduling problems with raw material constraints," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(6), pages 527-535, September.
    17. A. G. Leeftink & R. J. Boucherie & E. W. Hans & M. A. M. Verdaasdonk & I. M. H. Vliegen & P. J. Diest, 2018. "Batch scheduling in the histopathology laboratory," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 171-197, June.
    18. Yadong Wang & Baoqiang Fan & Jingang Zhai & Wei Xiong, 2019. "Two-machine flowshop scheduling in a physical examination center," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 363-374, January.
    19. Chen, Xin & Miao, Qian & Lin, Bertrand M.T. & Sterna, Malgorzata & Blazewicz, Jacek, 2022. "Two-machine flow shop scheduling with a common due date to maximize total early work," European Journal of Operational Research, Elsevier, vol. 300(2), pages 504-511.
    20. Wenchang Luo & Lin Chen & Guochuan Zhang, 2012. "Approximation schemes for two-machine flow shop scheduling with two agents," Journal of Combinatorial Optimization, Springer, vol. 24(3), pages 229-239, October.

    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:ijsaem:v:13:y:2022:i:3:d:10.1007_s13198-021-01411-5. 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.