Skip to main content
Conference Proceedings

Orebody Modelling and Strategic Mine Planning SMP 2014

Conference Proceedings

Orebody Modelling and Strategic Mine Planning SMP 2014

PDF Add to cart

Mineral Supply Chain Optimisation under Uncertainty Using Approximate Dynamic Programming

The optimisation of mine complexes and related value chains is a challenging problem due to the simultaneous presence of a highly-dimensional decision space, integer decision variables, non-linear constraints and recovery functions, as well as geological and market uncertainty. In addition, if the uncertainty is revealed progressively, then decisions need to continuously adapt to new information, which poses additional challenges. Stochastic dynamic programming is a well-known class of methods for addressing problems where a decision-maker reacts to new information. While simplistic applications of dynamic programming using exact representations would be intractable for any realistic mine planning problem, new dynamic programming methods using approximate value function representations have been successfully implemented in the past to address problems of similar complexity. This work formulates the problem of mine complex optimisation as an approximate dynamic program and presents an application of the resulting method to a gold-copper deposit.CITATION:Paduraru, C and Dimitrakopoulos, R, 2014. Mineral supply chain optimisation under uncertainty using approximate dynamic programming, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 415-422 (The Australasian Institute of Mining and Metallurgy: Melbourne).
Return to parent product
  • Mineral Supply Chain Optimisation under Uncertainty Using Approximate Dynamic Programming
    PDF
    This product is exclusive to Digital library subscription
  • Mineral Supply Chain Optimisation under Uncertainty Using Approximate Dynamic Programming
    PDF
    Normal price $22.00
    Member price from $0.00
    Add to cart

    Fees above are GST inclusive

PD Hours
Approved activity
  • Published: 2014
  • PDF Size: 1.253 Mb.
  • Unique ID: P201413047

Our site uses cookies

We use these to improve your browser experience. By continuing to use the website you agree to the use of cookies.