Optimised decision-making under grade uncertainty in surface mining
dc.contributor.author | Grobler, Francois | |
dc.contributor.supervisor | Dr Jose Saavedra-Rosas | |
dc.contributor.supervisor | Prof. Louis Caccetta | |
dc.date.accessioned | 2017-01-30T10:04:46Z | |
dc.date.available | 2017-01-30T10:04:46Z | |
dc.date.created | 2016-03-21T08:57:40Z | |
dc.date.issued | 2015 | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/1376 | |
dc.description.abstract |
Mining schedule optimisation often ignores geological and economic risks in favour of simplistic deterministic methods. In this thesis a scenario optimisation approach is developed which uses MILP optimisation results from multiple conditional simulations of geological data to derive a unique solution. The research also generated an interpretive framework which incorporates the use of the Coefficient of Variation allowing the assessment of various optimisation results in order to find the solution with the most attractive risk-return ratio. | |
dc.language | en | |
dc.publisher | Curtin University | |
dc.title | Optimised decision-making under grade uncertainty in surface mining | |
dc.type | Thesis | |
dcterms.educationLevel | PhD | |
curtin.department | Department of Mathematics & Statistics | |
curtin.accessStatus | Open access |