IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-00771482.html
   My bibliography  Save this paper

Using multistage stochastic optimisation to manage major production incidents

Author

Listed:
  • Margaret Armstrong

    (CERNA i3 - Centre d'économie industrielle i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris sciences et lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Alain Galli

    (CERNA i3 - Centre d'économie industrielle i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris sciences et lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Rija Razanatsimba

    (CERNA i3 - Centre d'économie industrielle i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris sciences et lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

Abstract

A mining company has entered into contractual commitments to supply certain quantities to clients in each time period. The planned production would be sufficient unless major problems that interrupt production occur. To overcome these difficulties, the Company may be able to obtain more of the commodity: from its strategic stockpile (if there is sufficient there), by buying it on the spot market or for some commodities such as gold and uranium, by leasing it. Two sources of uncertainty, the spot price of the commodity and the occurrence of serious production incidents are considered. Multistage stochastic programming with recourse was used to solve this problem, because in addition to providing the dollar value of the project, it gives decision-makers the 'roadmap' to reach the optimal value. A case study over a 5-year period is used to illustrate the proposed procedure.

Suggested Citation

  • Margaret Armstrong & Alain Galli & Rija Razanatsimba, 2012. "Using multistage stochastic optimisation to manage major production incidents," Post-Print hal-00771482, HAL.
    • Handle: RePEc:hal:journl:hal-00771482
    DOI: 10.1179/1743286312Y.0000000010
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Reus, Lorenzo & Pagnoncelli, Bernardo & Armstrong, Margaret, 2019. "Better management of production incidents in mining using multistage stochastic optimization," Resources Policy, Elsevier, vol. 63(C), pages 1-1.

    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:hal:journl:hal-00771482. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.