Exploitation
Meisam Saleki; Reza Khaloo Kakaie; Mohammad Ataei; Ali Nouri Qarahasanlou
Abstract
One of the most critical designs in open-pit mining is the ultimate pit limit (UPL). The UPL is frequently computed initially through profit-maximizing algorithms like the Lerchs-Grossman (LG). Then, in order to optimize net present value (NPV), production planning is executed for the blocks that ...
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One of the most critical designs in open-pit mining is the ultimate pit limit (UPL). The UPL is frequently computed initially through profit-maximizing algorithms like the Lerchs-Grossman (LG). Then, in order to optimize net present value (NPV), production planning is executed for the blocks that fall within the designated pit limit. This paper presents a mathematical model of the UPL with NPV maximization, enabling simultaneous determination of the UPL and long-term production planning. Model behavior is nonlinear. Thus, in order to achieve model linearization, the model has been partitioned into two linear sub-problems. The procedure facilitates the model solution and the strategy by decreasing the number of decision variables. Naturally, the model is NP-Hard. As a result, in order to address the issue, the Dynamic Pit Tracker (DPT) heuristic algorithm was devised, accepting economic block models as input. A comparison is made between the economic values and positional weights of blocks throughout the steps in order to identify the most appropriate block. The outcomes of the mathematical model, LG, and Latorre-Golosinski (LAGO) algorithms were assessed in relation to the DPT on a two-dimensional block model. Comparative analysis revealed that the UPLs generated by these algorithms are consistent in this instance. Utilizing the new algorithm to determine UPL for a 3D block model revealed that the final pit profit matched LG UPL by 97.95%.
M. Shenavar; M. Ataee-pour; M. Rahmanpour
Abstract
Production scheduling in underground mines is still a manual process, and achieving a truly optimal result through manual scheduling is impossible due to the complexity of the scheduling problems. Among the underground mining methods, sub-level caving is a common mining method with a high production ...
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Production scheduling in underground mines is still a manual process, and achieving a truly optimal result through manual scheduling is impossible due to the complexity of the scheduling problems. Among the underground mining methods, sub-level caving is a common mining method with a high production rate for hard rock mining. There are limited studies about long-term production scheduling in the sub-level caving method. In this work, for sub-level caving production scheduling optimization, a new mathematical model with the objective of net present value (NPV) maximization is developed. The general technical and operational constraints of the sub-level caving method such as opening and developments, production capacity, sub-level mining geometry, and ore access are considered in this model. Prior to the application of the scheduling model, the block model is processed to remove the unnecessary blocks. For this purpose, the floating stope algorithm is applied in order to determine the ultimate mine boundary and reduce the number of blocks that consequently reduces the running time of the model. The model is applied to a bauxite mine block model and the maximum NPV is determined, and then the mine development network is designed based on the optimal schedule.
Ali Asghar khodaiari; A Jafarnejad
Abstract
Maximizing economic earnings is the most common goal in cut-off grade optimization of open-pit mining operations. When this is the case, the price of the product has a critical effect on optimum value of cut-off grade. This paper investigates the relationship between optimum cut-off grade and price to ...
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Maximizing economic earnings is the most common goal in cut-off grade optimization of open-pit mining operations. When this is the case, the price of the product has a critical effect on optimum value of cut-off grade. This paper investigates the relationship between optimum cut-off grade and price to maximize total cash flow and net percent value (NPV) of operation. In order to visualize this relationship, two hypothetical mines were employed. To determine the optimum value of cut-off grade in different cases, two nonlinear programming models were formulated, and then, all models were solved using Solver in Excel. The results show that the optimum cut-off grade would always be a descending function of price when we intend to maximize total cash flow. On the other hand, this function may be descending or ascending when we intend to maximize NPV. This result also reveals that both maximum cash flow and maximum NPV always increase and decrease, respectively when the price of product increases or decreases.
