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dc.contributor.authorGrobler, Francois
dc.contributor.supervisorDr Jose Saavedra-Rosas
dc.contributor.supervisorProf. Louis Caccetta
dc.date.accessioned2017-01-30T10:04:46Z
dc.date.available2017-01-30T10:04:46Z
dc.date.created2016-03-21T08:57:40Z
dc.date.issued2015
dc.identifier.urihttp://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.languageen
dc.publisherCurtin University
dc.titleOptimised decision-making under grade uncertainty in surface mining
dc.typeThesis
dcterms.educationLevelPhD
curtin.departmentDepartment of Mathematics & Statistics
curtin.accessStatusOpen access


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