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Adaptive Simultaneous Stochastic Optimization of the Escondida Mining Complex, Chile
Indexado
WoS WOS:001319505700001
Scopus SCOPUS_ID:85204761705
DOI 10.1007/S42461-024-01092-1
Año 2024
Tipo artículo de investigación

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras


Abstract



This paper presents the application of adaptive simultaneous stochastic optimization with a representative branching framework to generate a strategic mining plan for the Escondida mining complex, the world's largest copper-production operation. This adaptive stochastic optimization considers geological uncertainty while integrating investment and operational alternatives in the production schedule of a mining complex. Mining complexes are comprised of interconnected components affected by multiple sources of uncertainty. Thus, they must be optimized simultaneously in order to maximize their value, manage environmental impacts, and minimize risk. Additionally, due to the extensive lives of assets and the dynamic and uncertain environment in which mining complexes operate, it is not reasonable to assume that the current strategic plan will remain optimal. Thus, an operationally feasible method to embed alternatives in the mine plan is used. The method utilized provides a strategic plan with representative branches for future possible investment decisions. Adaptive decisions are made sequentially over time, activating costs and effects over the model. The optimization process chooses the optimal strategic production plan accordingly, as well as the investments made and their timing. The Escondida mining complex is a multi-element, multi-pit operation with nine different processing destinations. Investment options considered herein are truck and shovel fleet sizing, adding a secondary crusher in one of the plants, and investing in a main crusher assigned to one of the pits. Additionally, operational alternatives at the mine and plant levels are included. The adaptive solution shows a substantial probability that the mine plan might change its design substantially due to geological uncertainty, presenting an increased expected net present value when compared to the previously developed stochastic mathematical programming formulation that does not consider adaptive decisions, thus generating a single static strategic production plan for the related mining complex. Further studies at the Escondida mining complex can consider adoptive solutions integrating capital investments pertinent to climate change issues.

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Disciplinas de Investigación



WOS
Metallurgy & Metallurgical Engineering
Mining & Mineral Processing
Scopus
Chemistry (All)
Materials Chemistry
Control And Systems Engineering
Mechanical Engineering
Geotechnical Engineering And Engineering Geology
Metals And Alloys
SciELO
Sin Disciplinas

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Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Colaboración Institucional



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Autores - Afiliación



Ord. Autor Género Institución - País
1 Del Castillo, M. Fernanda - MCGILL UNIV - Canadá
Université McGill - Canadá
2 Dimitrakopoulos, R. - MCGILL UNIV - Canadá
Université McGill - Canadá
3 Maulen, Marco - BHP - Chile
BHP Billiton - Chile

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Financiamiento



Fuente
Canada Research Chairs program
NSERC Discovery grant
COSMO Mining Industry Consortium
National Science and Engineering Research Council of Canada (NSERC) CRD

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Agradecimientos



Agradecimiento
This work is funded by the National Science and Engineering Research Council of Canada (NSERC) CRD Grant 500414-16, NSERC Discovery Grant 239019, the COSMO mining industry consortium (AngloGold Ashanti, Anglo American/DeBeers, Agnico Eagle, BHP, IAMGOLD, Kinross Gold, Newmont, and Vale), and the Canada Research Chairs Program.

Muestra la fuente de financiamiento declarada en la publicación.