TY  - JOUR
JF  - Systems
N2  - Traditional optimization of open pit mine design is a crucial component of mining endeavors and is influenced by many variables. The critical factor in optimization is the geological uncertainty, which relates to the ore grade. To deal with uncertainties related to the block economic values of mining blocks and the general problem of mine design optimization, under unknown conditions, the best ultimate pit limits and pushback designs are produced by a minimum cut algorithm. The push?relabel minimal cut algorithm provides a framework for computationally efficient representation and processing of the economic values of mining blocks under multiple scenarios. A sequential Gaussian simulation-based smoothing spline technique was created. To produce pushbacks, an efficient parameterized minimum cut algorithm is suggested. An analysis of Indian iron ore mining was performed. The developed mine scheduling algorithm was compared with the conventional algorithm, and the results show that when uncertainty is considered, the cumulative metal production is higher and there is an additional increase of about 5% in net present value. The results of this work help the mining industry to plan mines in such a way that can generate maximum profit from the deposits.
Y1  - 2022/09//
IS  - 5
VL  - 10
UR  - http://doi.org/10.3390/systems10050159
SN  - 2079-8954
ID  - uneatlantico4904
TI  - A Novel Large-Scale Stochastic Pushback Design Merged with a Minimum Cut Algorithm for Open Pit Mine Production Scheduling
A1  - Joshi, Devendra
A1  - Chithaluru, Premkumar
A1  - Singh, Aman
A1  - Yadav, Arvind
A1  - Elkamchouchi, Dalia H.
A1  - Mazas Pérez-Oleaga, Cristina
A1  - Anand, Divya
AV  - public
KW  - mine production scheduling; net present value; open pit mine; L-G algorithm; grade uncertainty; minimum cut algorithm
ER  -