IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v74y2001i1-3p135-146.html
   My bibliography  Save this article

A genetic approach to the scheduling of preventive maintenance tasks on a single product manufacturing production line

Author

Listed:
  • Cavory, G.
  • Dupas, R.
  • Goncalves, G.

Abstract

No abstract is available for this item.

Suggested Citation

  • Cavory, G. & Dupas, R. & Goncalves, G., 2001. "A genetic approach to the scheduling of preventive maintenance tasks on a single product manufacturing production line," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 135-146, December.
    • Handle: RePEc:eee:proeco:v:74:y:2001:i:1-3:p:135-146
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925-5273(01)00120-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. K A H Kobbacy & S Vadera & M H Rasmy, 2007. "AI and OR in management of operations: history and trends," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(1), pages 10-28, January.
    2. Quan, Gang & Greenwood, Garrison W. & Liu, Donglin & Hu, Sharon, 2007. "Searching for multiobjective preventive maintenance schedules: Combining preferences with evolutionary algorithms," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1969-1984, March.
    3. Coria, V.H. & Maximov, S. & Rivas-Dávalos, F. & Melchor, C.L. & Guardado, J.L., 2015. "Analytical method for optimization of maintenance policy based on available system failure data," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 55-63.
    4. Pedro J. Rivera Torres & Eileen I. Serrano Mercado & Orestes Llanes Santiago & Luis Anido Rifón, 2018. "Modeling preventive maintenance of manufacturing processes with probabilistic Boolean networks with interventions," Journal of Intelligent Manufacturing, Springer, vol. 29(8), pages 1941-1952, December.
    5. Khaled Alhamad & Yousuf Alkhezi & M. F. Alhajri, 2022. "Nonlinear Integer Programming for Solving Preventive Maintenance Scheduling Problem for Cogeneration Plants with Production," Sustainability, MDPI, vol. 15(1), pages 1-18, December.
    6. Song, Dong-Ping, 2009. "Production and preventive maintenance control in a stochastic manufacturing system," International Journal of Production Economics, Elsevier, vol. 119(1), pages 101-111, May.

    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:eee:proeco:v:74:y:2001:i:1-3:p:135-146. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.