3657 Underground mine stope boundary optimization using a hybrid network flow-particle swarm algorithm
DOI:
https://doi.org/10.17159/Abstract
This study introduced a new hybrid algorithm designed for optimizing the stope boundary in Sublevel stoping mines. Stopes were delineated based on raises' location and pertinent constraints, including minimal and maximal stope dimensions, stope overlapping, and geotechnical considerations. The particle swarm optimization algorithm was employed to determine the optimal location of raises, while a NFA applied constraints and generated stopes surrounding each raise, defining their size and shape. The hybrid algorithm was implemented on a copper deposit in Chile, situated 1000 meters below ground level. Comparative analysis against the network flow and maximum value neighbourhood algorithms demonstrated that the economic value of stopes derived from the hybrid algorithm surpasses that of the NFA by approximately 4%, and exceeds that of the maximum value neighbourhood algorithm by 7.5%. Moreover, the proposed algorithm exhibited the ability to ascertain stable stope layouts in large-scale problems within a reasonable timeframe. These findings are promising, particularly in light of the growing prevalence of high-tonnage, low-grade deposits in the mining industry.
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Copyright (c) 2026 Ahmadreza Esmaeili
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