IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v35y1987i2p185-197.html
   My bibliography  Save this article

Derived Demand and Capacity Planning Under Uncertainty

Author

Listed:
  • Eduardo Marco Modiano

    (Pontifícia Universidade Católica do Rio de Janeiro, Brazil)

Abstract

This paper is concerned with the derivation of demand functions for primary resources in an economic environment with uncertainty. This issue is critical when resource markets must decide, in the face of uncertainty, whether to expand capacity and/or to introduce new technologies. The models proposed are primarily data oriented. They explore two alternative behavioral models of action under uncertainty: here-and-now and wait-and-see . We present an application to the U.S. energy sector's demand for coal and the related expansion of capacity of coal-fired electricity generation plants.

Suggested Citation

  • Eduardo Marco Modiano, 1987. "Derived Demand and Capacity Planning Under Uncertainty," Operations Research, INFORMS, vol. 35(2), pages 185-197, April.
    • Handle: RePEc:inm:oropre:v:35:y:1987:i:2:p:185-197
    DOI: 10.1287/opre.35.2.185
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.35.2.185
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.35.2.185?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
    ---><---

    Citations

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


    Cited by:

    1. Stephan Nagl, Michaela Fursch, and Dietmar Lindenberger, 2013. "The Costs of Electricity Systems with a High Share of Fluctuating Renewables: A Stochastic Investment and Dispatch Optimization Model for Europe," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    2. Logan, Douglas M., 1990. "5.4. Decision analysis in engineering-economic modeling," Energy, Elsevier, vol. 15(7), pages 677-696.
    3. Kjetil Haugen & Stein Wallace, 2006. "Stochastic programming: Potential hazards when random variables reflect market interaction," Annals of Operations Research, Springer, vol. 142(1), pages 119-127, February.
    4. Stephan Nagl & Michaela Fürsch & Dietmar Lindenberger, 2013. "The Costs of Electricity Systems with a High Share of Fluctuating Renewables: A Stochastic Investment and Dispatch Optimization Model for Europe," The Energy Journal, , vol. 34(4), pages 151-180, October.
    5. C A Poojari & C Lucas & G Mitra, 2008. "Robust solutions and risk measures for a supply chain planning problem under uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(1), pages 2-12, January.
    6. Nagl, Stephan & Fürsch, Michaela & Lindenberger, Dietmar, 2012. "The costs of electricity systems with a high share of fluctuating renewables - a stochastic investment and dispatch optimization model for Europe," EWI Working Papers 2012-1, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).

    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:inm:oropre:v:35:y:1987:i:2:p:185-197. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.