Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming
Mixed Integer Programming (MIP) models are recognised as possessing the ability to optimise underground mine planning. However, MIP's use for optimising underground mine planning has often been restricted to problems of certain sizes and/or simplicity. This is because the number of variables an...
| Main Authors: | , |
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| Format: | Journal Article |
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INDERSIENCE
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/27503 |
| _version_ | 1848752281593315328 |
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| author | Little, J. Topal, Erkan |
| author_facet | Little, J. Topal, Erkan |
| author_sort | Little, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Mixed Integer Programming (MIP) models are recognised as possessing the ability to optimise underground mine planning. However, MIP's use for optimising underground mine planning has often been restricted to problems of certain sizes and/or simplicity. This is because the number of variables and complex constraints in MIP formulations influences the model's ability to generate optimal results. This paper reviews optimisation studies, focusing on model reduction approaches, which employ MIP techniques for simultaneous optimisation of stope layouts and underground production scheduling. Four theories are presented to reduce the number of variables and complex constraints without comprising its mathematical integrity. |
| first_indexed | 2025-11-14T08:06:08Z |
| format | Journal Article |
| id | curtin-20.500.11937-27503 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:06:08Z |
| publishDate | 2011 |
| publisher | INDERSIENCE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-275032017-09-13T15:52:28Z Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming Little, J. Topal, Erkan Mixed Integer Programming (MIP) models are recognised as possessing the ability to optimise underground mine planning. However, MIP's use for optimising underground mine planning has often been restricted to problems of certain sizes and/or simplicity. This is because the number of variables and complex constraints in MIP formulations influences the model's ability to generate optimal results. This paper reviews optimisation studies, focusing on model reduction approaches, which employ MIP techniques for simultaneous optimisation of stope layouts and underground production scheduling. Four theories are presented to reduce the number of variables and complex constraints without comprising its mathematical integrity. 2011 Journal Article http://hdl.handle.net/20.500.11937/27503 10.1504/IJMME.2011.042429 INDERSIENCE restricted |
| spellingShingle | Little, J. Topal, Erkan Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming |
| title | Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming |
| title_full | Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming |
| title_fullStr | Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming |
| title_full_unstemmed | Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming |
| title_short | Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming |
| title_sort | strategies to assist in obtaining an optimal solution for an underground mine planning problem using mixed integer programming |
| url | http://hdl.handle.net/20.500.11937/27503 |