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    Robust decision making - Application to mine planning under price uncertainty

    Access Status
    Fulltext not available
    Authors
    Grobler, Francois
    Elkington, T.
    Rendu, J.
    Date
    2011
    Type
    Conference Paper
    
    Metadata
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    Citation
    Grobler, F. and Elkington, T. and Rendu, J. 2011. Robust decision making - Application to mine planning under price uncertainty, pp. 371-380.
    Source Title
    35th APCOM Symposium - Application of Computers and Operations Research in the Minerals Industry, Proceedings
    ISBN
    9781921522512
    School
    Department of Mathematics and Statistics
    URI
    http://hdl.handle.net/20.500.11937/52437
    Collection
    • Curtin Research Publications
    Abstract

    Many projects fail because project performance in unfavourable economic conditions was not anticipated at the investment decision stage. This type of failure may have been avoided through the selection of a strategy that enables the project to perform well under a range of possible future economic conditions (a 'robust' strategy); rather than an 'optimal' strategy for expected future conditions that will never eventuate. This paper describes a method of rapidly generating mine plans for a number of project strategies, and then evaluating it against a representative range of equally likely economic conditions. The key performance indicators derived for each strategy are the mean value and the distribution of values (variance). A prudent investor will identify prospective strategies not only on the merit of highest mean values (as a proxy for economic reward), but also on the probability of not meeting specified investment hurdles (a proxy for risk). A robust strategy will achieve its financial objective even under adverse economic variations. This paper focuses on the effect of commodity price uncertainty; particularly around the choice of mining and processing capacity levels. Results from enumerating 2000 prices scenarios against 63 strategy combinations show how processing and mining capacity can be manipulated to manage the risk-reward trade-off.

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