Abstract
Mathematical programming has been applied to optimizing open pit mine planning problems since the early 1960s. Nonetheless, it still remains challenging to obtain a life-of-mine plan with current computational hardware and software, mostly because of the scale of the input data, which is generally in the form of mining blocks. To overcome this challenge, one common practice is to aggregate blocks into larger units before formulating and solving mine planning models. However, the majority of available block aggregation techniques ignore the slope relation between blocks or are simply not capable of controlling the number of aggregates generated. In this study, a new optimization method for open pit mine planning is proposed, which consists of two stages. In the first stage, a new block aggregation algorithm is proposed, called the TopCone algorithm (TCA), where blocks are clustered into TopCones (TCs), which have two important features: (1) the cone shape and (2) the number of TCs that can be explicitly controlled. In the second stage, TCs form the basis of an integer programming model with a variety of operational constraints so that a high-quality production scheduling solution can be obtained in relatively quick computational time. The capability and novelty of the proposed method is demonstrated through the optimization of the long-term production schedule of a large-scale copper deposit. The case study shows higher NPV results compared to a commercial software package, and the entire mine planning process can be completed in less than 10 minutes.
| Original language | English |
|---|---|
| Pages (from-to) | 705-714 |
| Number of pages | 10 |
| Journal | Journal of the Southern African Institute of Mining and Metallurgy |
| Volume | 118 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Jul 1 2018 |
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Keywords
- Integer programming
- Large-scale optimization
- Open pit mine planning
- Production scheduling
- TopCone algorithm
ASJC Scopus subject areas
- Geotechnical Engineering and Engineering Geology
- Metals and Alloys
- Materials Chemistry
Cite this
A new open-pit mine planning optimization method using block aggregation and integer programming. / Mai, N. L.; Topal, Erkan; Erten, O.
In: Journal of the Southern African Institute of Mining and Metallurgy, Vol. 118, No. 7, 01.07.2018, p. 705-714.Research output: Contribution to journal › Article
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TY - JOUR
T1 - A new open-pit mine planning optimization method using block aggregation and integer programming
AU - Mai, N. L.
AU - Topal, Erkan
AU - Erten, O.
PY - 2018/7/1
Y1 - 2018/7/1
N2 - Mathematical programming has been applied to optimizing open pit mine planning problems since the early 1960s. Nonetheless, it still remains challenging to obtain a life-of-mine plan with current computational hardware and software, mostly because of the scale of the input data, which is generally in the form of mining blocks. To overcome this challenge, one common practice is to aggregate blocks into larger units before formulating and solving mine planning models. However, the majority of available block aggregation techniques ignore the slope relation between blocks or are simply not capable of controlling the number of aggregates generated. In this study, a new optimization method for open pit mine planning is proposed, which consists of two stages. In the first stage, a new block aggregation algorithm is proposed, called the TopCone algorithm (TCA), where blocks are clustered into TopCones (TCs), which have two important features: (1) the cone shape and (2) the number of TCs that can be explicitly controlled. In the second stage, TCs form the basis of an integer programming model with a variety of operational constraints so that a high-quality production scheduling solution can be obtained in relatively quick computational time. The capability and novelty of the proposed method is demonstrated through the optimization of the long-term production schedule of a large-scale copper deposit. The case study shows higher NPV results compared to a commercial software package, and the entire mine planning process can be completed in less than 10 minutes.
AB - Mathematical programming has been applied to optimizing open pit mine planning problems since the early 1960s. Nonetheless, it still remains challenging to obtain a life-of-mine plan with current computational hardware and software, mostly because of the scale of the input data, which is generally in the form of mining blocks. To overcome this challenge, one common practice is to aggregate blocks into larger units before formulating and solving mine planning models. However, the majority of available block aggregation techniques ignore the slope relation between blocks or are simply not capable of controlling the number of aggregates generated. In this study, a new optimization method for open pit mine planning is proposed, which consists of two stages. In the first stage, a new block aggregation algorithm is proposed, called the TopCone algorithm (TCA), where blocks are clustered into TopCones (TCs), which have two important features: (1) the cone shape and (2) the number of TCs that can be explicitly controlled. In the second stage, TCs form the basis of an integer programming model with a variety of operational constraints so that a high-quality production scheduling solution can be obtained in relatively quick computational time. The capability and novelty of the proposed method is demonstrated through the optimization of the long-term production schedule of a large-scale copper deposit. The case study shows higher NPV results compared to a commercial software package, and the entire mine planning process can be completed in less than 10 minutes.
KW - Integer programming
KW - Large-scale optimization
KW - Open pit mine planning
KW - Production scheduling
KW - TopCone algorithm
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UR - http://www.scopus.com/inward/citedby.url?scp=85053601930&partnerID=8YFLogxK
U2 - 10.17159/2411-9717/2018/v118n7a4
DO - 10.17159/2411-9717/2018/v118n7a4
M3 - Article
VL - 118
SP - 705
EP - 714
JO - Journal of the Southern African Institute of Mining and Metallurgy
JF - Journal of the Southern African Institute of Mining and Metallurgy
SN - 2225-6253
IS - 7
ER -