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Open-pit mining with uncertainty: A conditional value-at-risk approach
University of Cape Coast, Ghana .
Linköpings universitet, Matematiska institutionen, Optimeringslära. Linköpings universitet, Tekniska högskolan.ORCID-id: 0000-0003-2094-7376
Linköpings universitet, Matematiska institutionen, Matematik och tillämpad matematik. Linköpings universitet, Tekniska högskolan.
2013 (Engelska)Ingår i: Optimization Theory, Decision Making, and Operations Research Applications: Proceedings of the 1st International Symposium and 10th Balkan Conference on Operational Research / [ed] Athanasios Migdalas, Angelo Sifaleras, Christos K. Georgiadis, Jason Papathanasiou, Emmanuil Stiakakis, New York: Springer, 2013, s. 117-139Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

The selection of a mine design is based on estimating net present values of all possible, technically feasible mine plans so as to select the one with the maximum value. It is a hard task to know with certainty the quantity and quality of ore in the ground. This geological uncertainty and also the future market behavior of metal prices and foreign exchange rates, which are always uncertain, make mining a high risk business. Value-at-Risk (VaR) is a measure that is used in financial decisions to minimize the loss caused by inadequate monitoring of risk. This measure does, however, have certain drawbacks such as lack of consistency, nonconvexity, and nondifferentiability. Rockafellar and Uryasev [J. Risk 2, 21-41 (2000)] introduce the Conditional Value-at-Risk (CVaR) measure as an alternative to the VaR measure. The CVaR measure gives rise to a convex optimization problem. An optimization model that maximizes expected return while minimizing risk is important for the mining sector as this will help make better decisions on the blocks of ore to mine at a particular point in time. We present a CVaR approach to the uncertainty involved in open-pit mining. We formulate investment and design models for the open-pit mine and also give a nested pit scheduling model based on CVaR. Several numerical results based on our models are presented by using scenarios from simulated geological and market uncertainties.

Ort, förlag, år, upplaga, sidor
New York: Springer, 2013. s. 117-139
Serie
Springer Proceedings in Mathematics and Statistics, ISSN 2194-1009 ; 31
Nationell ämneskategori
Matematik
Identifikatorer
URN: urn:nbn:se:liu:diva-106239DOI: 10.1007/978-1-4614-5134-1_8ISBN: 978-146145133-4 (print) (tryckt)ISBN: 978-1-4614-5134-1 (tryckt)OAI: oai:DiVA.org:liu-106239DiVA, id: diva2:714909
Konferens
1st International Symposium and 10th Balkan Conference on Operational Research, 22-25 September 2011, Thessaloniki, Greece
Tillgänglig från: 2014-04-29 Skapad: 2014-04-29 Senast uppdaterad: 2014-05-08Bibliografiskt granskad

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Amankwah, HenryLarsson, TorbjörnTextorius, Björn

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