A OPEN PIT MINING AÇIK OCAK MADENCİLİĞİ

contains 94’311 blocks. In this section the
following assumptions are made:
a) The mine is not processing the ore
blocks in the plant
b) The mine is producing blended ore to the
market
c) There is no limit on the demand for the
product
d) The mine should produce a blended
product with a quality of minimum 65%
of Fe, and 0.15% of P and 0.2% of S in
maximum.
Figure 3. Ore body model of Gol-e-Gohar
iron ore mine number 2
The grade-tonnage curves and curves for
cut-off iron versus average iron, sulfur, and
phosphor is generated for the deposit (Figure
4).
content. Therefore, the constraint on P
content is relaxed for all the blended
products. This graph is used to determine the
cut-off grade of iron in accordance with the
blend requirements. Based on this graph and
the traditional way of selecting ore blocks, a
cutoff grade of 61% of Fe content satisfies
final product requirements. Based on the
determined cutoff grade, 346 blocks were
selected as ore blocks. After recognizing of
ore blocks, the block economic value of
these blocks were assigned to be equal to the
value of final product and the economic
value of other block were assigned as waste
blocks. The economic block model is then
fed into a pit limit optimizer. In this paper,
maximum flow algorithm was used to
optimize the ultimate pit limit (as in Osanloo
et al. 2010). Using the technique, the
optimized pit limit contains 6383 block
which 336 of them are ore blocks.
The aim of this work is to design an
optimized pit-blend limit. To do so, the
procedure described in figure 1 is applied to
the block model of Gol-e-Gohar iron ore
deposit. The mathematical model (equations
2-5) is solved by jDE algorithm, to optimize
the selection of blocks that meets the
blending requirements.
Solving the blend optimization model,
2015 blocks are selected as potential ore
block to be fed into the pit optimizer. The
selected blocks satisfy the requirements of
blended product. Then the economic block
model is constructed and fed into a pit limit
optimizer. Using maximum flow algorithm,
the optimal pit of the mine is determined. On
the final iteration of the procedure, the
optimized pit limit contains 26083 blocks
which 1995 blocks of them are ore blocks.
The ultimate pit limit of the optimized pitblend
limit and the pit determined by
traditional method (Mol and Gillies, 1984) is
shown in figure 5 and 6.
Figure 4. Grade tonnage curves of the
deposit
According to the grade-tonnage curves, all
of the ore blocks satisfy the constraint of P
Figure 5. Perspective of ultimate pit limit
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