Heuristics for integrated blending optimisation in a mining supply chain

Haonan, Zhou; Samavati, Mehran; Hill, Andrew

doi:10.1016/j.omega.2020.102373

Cited by 8 publications

(1 citation statement)

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“…The authors proposed the consideration of environmental variables in the determination of 𝐶𝑂𝐺𝑠. Few authors emphasized the importance and integration of blending optimization throughout the mining value chain (Chanda & Dagdelen, 1995;Haonan et al, 2021;Jamshidi & Osanloo, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

A new global optimum solution model based on multi-value dynamic programming for the cut-off grade optimization in a surface mining complex

Biswas

Sinha

Sen

2021

Preprint

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In techno-economic concern, cut-off grade (COG) optimization is the key for efficient mineral liquidation from thehuge metalliferous surface mining sector. In this paper, a sequentially advancing algorithm based on discretemulti-value dynamic programming (MDP) has been developed to calculate the global optimum COG of alarge-scale open-pit metalliferous deposit. The proposed COG optimization algorithm aims to overcome thelimitations of straightforward classical techniques in determining the optimum COG. This discrete COG-MDPmodel is the first of its kind and has the novelty of dealing with the simulation of eight dynamic possibilities toachieve the maximal global Net Present Value (NPV). A high-level programming language (Python) has been usedto develop the computer model to deal with the complexity of handling a minimum of 500 series of dynamicvariables. This model can generate results in polynomial-time from the complex of mining, milling, and smeltingand refining system corresponding to various limiting conditions. The prime objective considered in the model isto optimize the COG of a metalliferous deposit. A working open-pit copper mining complex from India has beenused to validate the model. In this study, the optimum COG for the Malanjkhand copper deposit has been found tobe (0.33%, 0.23%, 0.52%, 0.26%, 0.27%, 0.22%, 0.24%) with a maximum NPV of ₹ (12204, 14653, 16948, 14609,21454, 26717, 38821) million corresponding to various scenarios. The findings also show that the present valuegradually hits zero after the project’s life cycle, confirming the typical pattern of other mining firms.

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Section: Literature Reviewmentioning

confidence: 99%