Digitized by Kansas Correctional Industries

Thesis (M.S.)--West Virginia University, 2001. / Title from document title page. Document formatted into pages; contains x, 64 p. : ill. (some col.), maps. Includes abstract. Includes bibliographical references (p. 63-64).

Thesis (M. Sc.)--University of Queensland, 2002. / Includes bibliographical references.

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The mine production schedule defines the sequence of extraction of selected mine units over the life of the mine, and consequentially establishes the ore supply and total material movement. This sequence should be optimized so as to maximize the overall discounted value of the project. Conventional schedule approaches are unable to incorporate grade uncertainty into the scheduling problem formulation and may lead to serious deviations from forecasted production targets. Stochastic mine production schedulers are considered to obtain more robust mine production schedule solutions. / The application of stochastic approaches to the mine production schedule problem is recent and additional testing is required to better understand these tools and to define the value of a stochastic solution as compared to the conventional result. Two stochastic schedulers are tested in a low-grade variability copper deposit, optimization parameters are discussed and their results compared with a conventional schedule. / The first method uses a stochastic combinatorial optimization approach based on simulated annealing to address the mine production schedule problem. The method aims for maximization of the net present value (NPV) of the project and minimization of deviations from the production targets. These objectives are attained by incorporating grade uncertainty into the mine production schedule problem formulation. The second method formulates the problem as a stochastic integer programming problem, in which the objective is the maximization of the projects' NPV and the minimization of production targets deviations. The model can also manage how the risk of deviating from the targets is distributed between production periods. / Both stochastic approaches were tested in a low-grade variability copper deposit. In both case studies, the value of a stochastic solution is demonstrated to be higher than the conventional one. This fact demonstrated the misleading results that a conventional schedule may produce and shows the importance of not ignoring the presence of uncertainty when defining the mine production schedule for a project.

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