IDEAS home Printed from https://ideas.repec.org/a/wly/jnljam/v2013y2013i1n720607.html

A Fuzzy Nonlinear Programming Approach for Optimizing the Performance of a Four‐Objective Fluctuation Smoothing Rule in a Wafer Fabrication Factory

Author

Listed:
  • Horng-Ren Tsai
  • Toly Chen

Abstract

In theory, a scheduling problem can be formulated as a mathematical programming problem. In practice, dispatching rules are considered to be a more practical method of scheduling. However, the combination of mathematical programming and fuzzy dispatching rule has rarely been discussed in the literature. In this study, a fuzzy nonlinear programming (FNLP) approach is proposed for optimizing the scheduling performance of a four‐factor fluctuation smoothing rule in a wafer fabrication factory. The proposed methodology considers the uncertainty in the remaining cycle time of a job and optimizes a fuzzy four‐factor fluctuation‐smoothing rule to sequence the jobs in front of each machine. The fuzzy four‐factor fluctuation‐smoothing rule has five adjustable parameters, the optimization of which results in an FNLP problem. The FNLP problem can be converted into an equivalent nonlinear programming (NLP) problem to be solved. The performance of the proposed methodology has been evaluated with a series of production simulation experiments; these experiments provide sufficient evidence to support the advantages of the proposed method over some existing scheduling methods.

Suggested Citation

  • Horng-Ren Tsai & Toly Chen, 2013. "A Fuzzy Nonlinear Programming Approach for Optimizing the Performance of a Four‐Objective Fluctuation Smoothing Rule in a Wafer Fabrication Factory," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnljam:v:2013:y:2013:i:1:n:720607
    DOI: 10.1155/2013/720607
    as

    Download full text from publisher

    File URL: https://doi.org/10.1155/2013/720607
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2013/720607?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
    ---><---

    References listed on IDEAS

    as
    1. Hong Chen & David D. Yao, 1993. "Dynamic Scheduling of a Multiclass Fluid Network," Operations Research, INFORMS, vol. 41(6), pages 1104-1115, December.
    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. Haifang Cheng & Weilai Huang & Jianhu Cai, 2013. "Solving a Fully Fuzzy Linear Programming Problem through Compromise Programming," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    2. Toly Chen & Yi-Chi Wang, 2013. "A Fuzzy Rule for Improving the Performance of Multiobjective Job Dispatching in a Wafer Fabrication Factory," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).

    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. Lun Yu & Seyed Iravani & Ohad Perry, 2025. "Asymptotically Optimal Clearing Control of Backlogs in Multiclass Processing Systems," Operations Research, INFORMS, vol. 73(4), pages 2061-2078, July.
    2. Noa Zychlinski, 2023. "Applications of fluid models in service operations management," Queueing Systems: Theory and Applications, Springer, vol. 103(1), pages 161-185, February.
    3. J. G. Dai & Gideon Weiss, 2002. "A Fluid Heuristic for Minimizing Makespan in Job Shops," Operations Research, INFORMS, vol. 50(4), pages 692-707, August.
    4. Maglaras, Constantinos & Van Mieghem, Jan A., 2005. "Queueing systems with leadtime constraints: A fluid-model approach for admission and sequencing control," European Journal of Operational Research, Elsevier, vol. 167(1), pages 179-207, November.
    5. Junfei Huang & Boaz Carmeli & Avishai Mandelbaum, 2015. "Control of Patient Flow in Emergency Departments, or Multiclass Queues with Deadlines and Feedback," Operations Research, INFORMS, vol. 63(4), pages 892-908, August.
    6. Zerui Wu & Ran Liu & Ershun Pan, 2023. "Server Routing-Scheduling Problem in Distributed Queueing System with Time-Varying Demand and Queue Length Control," Transportation Science, INFORMS, vol. 57(5), pages 1209-1230, September.
    7. Constantinos Maglaras, 2006. "Revenue Management for a Multiclass Single-Server Queue via a Fluid Model Analysis," Operations Research, INFORMS, vol. 54(5), pages 914-932, October.
    8. Yang, Jun & Yan, Houmin & Sethi, Suresh P., 1999. "Optimal production planning in pull flow lines with multiple products," European Journal of Operational Research, Elsevier, vol. 119(3), pages 582-604, December.
    9. J. G. Dai & Wuqin Lin, 2005. "Maximum Pressure Policies in Stochastic Processing Networks," Operations Research, INFORMS, vol. 53(2), pages 197-218, April.
    10. Dragos Florin Ciocan & Vivek Farias, 2012. "Model Predictive Control for Dynamic Resource Allocation," Mathematics of Operations Research, INFORMS, vol. 37(3), pages 501-525, August.
    11. Yoni Nazarathy & Gideon Weiss, 2009. "Near optimal control of queueing networks over a finite time horizon," Annals of Operations Research, Springer, vol. 170(1), pages 233-249, September.
    12. Dimitris Bertsimas & David Gamarnik & Jay Sethuraman, 2003. "From Fluid Relaxations to Practical Algorithms for High-Multiplicity Job-Shop Scheduling: The Holding Cost Objective," Operations Research, INFORMS, vol. 51(5), pages 798-813, October.

    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:wly:jnljam:v:2013:y:2013:i:1:n:720607. 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: Wiley Content Delivery (email available below). General contact details of provider: https://onlinelibrary.wiley.com/journal/4185 .

    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.