A. Kumar, R. Dimitrakopoulos
This research addresses the integration of geometallurgical constraints into the simultaneous stochastic optimization of mining complexes, specifically applied to the Escondida mining complex in Chile. The objective is to enhance decision-making processes in resource extraction by incorporating geological and metallurgical variability into optimization models. A novel methodology is developed that combines stochastic optimization techniques with geometallurgical considerations, allowing for a more comprehensive evaluation of mining operations. The study incorporates data from various sources, including geological surveys and metallurgical test results, to create a robust optimization framework. The results demonstrate significant improvements in the performance of mining operations when geometallurgical constraints are factored into the optimization process. The practical implications of such integrated models are highlighted, showcasing potential increases in resource recovery and reductions in operational costs. This work contributes to the growing field of computational geosciences and offers valuable insights for stakeholders in the mining industry seeking to adopt more efficient and sustainable practices.
@article{e563cb57-1d70-44a9-b122-0a9b92b98b1b,
title={Expanding simultaneous stochastic optimi},
author={A. Kumar and R. Dimitrakopoulos},
year={2026},
language={en}
}TY - JOUR TI - Expanding simultaneous stochastic optimi AU - A. Kumar AU - R. Dimitrakopoulos PY - 2026 LA - en ER -
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