Integrated optimization of stope boundary selection and scheduling for sublevel stoping operations

Copland, T. and Nehring, M. (2016) Integrated optimization of stope boundary selection and scheduling for sublevel stoping operations. The Journal of the South African Institute of Mining and Metallurgy, 116 12: 1135-1142. doi:10.17159/2411-9717/2016/v116n12a7


Author Copland, T.
Nehring, M.
Title Integrated optimization of stope boundary selection and scheduling for sublevel stoping operations
Journal name The Journal of the South African Institute of Mining and Metallurgy   Check publisher's open access policy
ISSN 2225-6253
2411-9717
Publication date 2016-12-01
Sub-type Article (original research)
DOI 10.17159/2411-9717/2016/v116n12a7
Open Access Status DOI
Volume 116
Issue 12
Start page 1135
End page 1142
Total pages 8
Place of publication Johannesburg South Africa
Publisher Southern African Institute of Mining and Mettallurgy
Collection year 2017
Language eng
Abstract The decreasing availability of resources amenable to surface operations has led to increasing numbers of underground mines, with trends indicating this will continue into the future. As a result, there is a need for additional optimization processes and techniques for underground mines, with many analogous methods having already been developed for surface mining. Current methods for design and optimization of stope boundary selection and scheduling mainly involve heuristic methods which focus on a single lever. Individual optimality may be approached, but globally optimal results can be obtained only by an integrated, rigorous approach. In this paper we review previous methodologies for stope boundary selection and medium- to long-term scheduling and highlight the need for an integrated approach. Previous integrated approaches are reviewed and an improved modelling system proposed for shorter solution times and greater applicability to mining situations. Randomly generated data-sets for gold-copper mineralization are used to investigate the model performance, describing solution time as a function of data complexity.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mechanical & Mining Engineering Publications
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Created: Wed, 01 Mar 2017, 15:42:24 EST by Clare Nelson on behalf of School of Mechanical and Mining Engineering