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Communication

Reducing the Dimensions of the Stochastic Programming Problems of Metallurgical Design Procedures

Escuela de Ingeniería Química, Pontificia Universidad Católica de Valparaíso, Valparaíso 2340000, Chile
Academic Editor: Chiharu Tokoro
Minerals 2021, 11(12), 1302; https://doi.org/10.3390/min11121302
Received: 27 October 2021 / Revised: 17 November 2021 / Accepted: 19 November 2021 / Published: 23 November 2021
Process design procedures under uncertainty result in stochastic optimization problems whose resolution is complex due to the large uncertainty space, which hinders the application of optimization approaches, as well as the establishment of relationships between input and output variables. On the other hand, supervised machine learning (SML) offers tools with which to develop surrogate models, which are computationally inexpensive and efficient. This paper proposes a procedure based on modern design of experiments, deterministic optimization, SML tools, and global sensitivity analysis (GSA) to reduce the size of the uncertainty space for stochastic optimization problems. The proposal is illustrated with a case study based on the stochastic design of flotation plants. The results reveal that surrogate models of stochastic formulation enable the prediction of the structure, profitability parameters, and metallurgical parameters of designed flotation plants, as well as reducing the size of the uncertainty space via GSA and, consequently, establishing relationships between the input and output variables of the stochastic formulation. View Full-Text
Keywords: stochastic optimization; supervised machine learning; global sensitivity stochastic optimization; supervised machine learning; global sensitivity
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MDPI and ACS Style

Lucay, F.A. Reducing the Dimensions of the Stochastic Programming Problems of Metallurgical Design Procedures. Minerals 2021, 11, 1302. https://doi.org/10.3390/min11121302

AMA Style

Lucay FA. Reducing the Dimensions of the Stochastic Programming Problems of Metallurgical Design Procedures. Minerals. 2021; 11(12):1302. https://doi.org/10.3390/min11121302

Chicago/Turabian Style

Lucay, Freddy A. 2021. "Reducing the Dimensions of the Stochastic Programming Problems of Metallurgical Design Procedures" Minerals 11, no. 12: 1302. https://doi.org/10.3390/min11121302

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