A mixed-integer linear programming model for the stockpiles blending problem in a nickel mine. (5th January 2023)

• Record Type: Journal Article
• Authors: Silva, Arlem; Beneteli, Tatianna Aparecida Pereira; Silva, Luiz; Pessin, Gustavo; Euzébio, Thiago Antônio Melo; Cota, Luciano Perdigão
• Is Part Of: International journal of mining and mineral engineering. Volume 13:Number 2(2022)
• Page Start: 93
• Page End: 118
• Publication Date: 2023-01-05
• Subjects: open-pit mining -- blending -- stockpiles -- mixed-integer linear programming model -- decision support system; Mining engineering -- Periodicals; Mines and mineral resources -- Periodicals; 622.05
• Languages: English
• ISSNs: 1754-890X

Abstract

This work addresses the problem of stockpiles blending in a nickel mine. In the literature, many studies address the ore blending problem in iron and coal mines; however, research on nickel mines is scarce. The pyrometallurgical process, used in nickel mines, requires better blend quality control, imposing some singularities in the mining process, such as stacking the ore extracted from the mining fronts in stockpiles. The stored ore is blended to feed the processing plant. The optimisation problem seeks to minimise the deviation from the total mass target, the deviations from the grade targets, and the number of used stockpiles. We propose a mixed-integer linear programming model to solve the problem. In the computational experiments, we use five real scenarios of a Brazilian nickel mine. The results show that the mathematical model implemented in solver finds optimal solutions in a few seconds, demonstrating the proposal's accuracy as a decision support system.