Please use this identifier to cite or link to this item: https://knowledgecommons.lakeheadu.ca/handle/2453/5064
Title: Advances in operations research models used in the gold mining industry
Authors: Gliwan, Suliman Emdini
Keywords: Underground gold mine;Operations research;Optimization models
Issue Date: 2023
Abstract: The topic addressed in this dissertation is a set of economically important operational problems in the gold mining industry that are solved using mathematical models of operations research. More specifically, the main objective of this thesis is to formulate and evaluate decision support models for three important diverse challenges which were found to exist at an underground gold mine in Northwestern Ontario: Newmont Goldcorp’s Red Lake Gold Mine. The challenges discovered at Red Lake Gold Mine are not peculiar to that location but are economically relevant to the underground gold mining industry in as whole. The mine at Red Lake provided a deeper understanding of the problems and data sets. The challenges modeled and solved in this dissertation are: i. minimizing freshwater used in the processing of gold ore; ii. optimizing ore-waste material flow in an underground gold mine; and iii. optimal dispatching of trucks and shovels in an underground gold mine. Each of the three problems was treated with a formulation of the model which is innovative and the evaluation of the results of each case study showed that improved decisions can result when these models are used. This dissertation shows that, for a single gold mine, problems of major economic importance can be found, innovatively modeled, and solved using the methods of operations research. In addition, since these problems are not peculiar to one gold mine, but are found in other gold mines, the innovation of this dissertation is relevant to the underground gold mining industry as a whole and therefore constitutes a minor but important advance in the practical knowledge in this industry
URI: https://knowledgecommons.lakeheadu.ca/handle/2453/5064
metadata.etd.degree.discipline: Natural Resources Management
metadata.etd.degree.name: Doctor of Philosophy
metadata.etd.degree.level: Doctoral
metadata.dc.contributor.advisor: Crowe, Kevin
metadata.dc.contributor.committeemember: Amishev, Dzhamal
Ellhamidi, Nuri
Appears in Collections:Electronic Theses and Dissertations from 2009

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