Environment
Amir Batarbiat; Mojtaba Rezakhah; Vahid Vaziri
Abstract
This paper proposes an integrated optimization–fuzzy multi-criteria decision-making framework to support the sustainable management of waste rock and tailings in an open-pit gold mine. Mine waste management is formulated as six mutually exclusive allocation scenarios (A₁–A₆), each specifying ...
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This paper proposes an integrated optimization–fuzzy multi-criteria decision-making framework to support the sustainable management of waste rock and tailings in an open-pit gold mine. Mine waste management is formulated as six mutually exclusive allocation scenarios (A₁–A₆), each specifying which overburden dumps and tailings storage facilities (TSFs) are available over a 12-month planning horizon divided into monthly periods. For each scenario, an optimization layer generates auditable operational plans using two linear programs: Model C, which minimizes controllable operating costs, and Model E, which minimizes a composite environmental impact index constructed from four routing-sensitive indicators—water consumption, haul-road dust emissions, TSF stability risk, and acid mine drainage potential. Uncertainty in inputs and qualitative assessments is represented using triangular fuzzy numbers and propagated via α-cuts. The resulting fuzzy performance matrix encompasses eleven criteria spanning economic, environmental, operational, technical, and social aspects; criteria are weighted using Fuzzy AHP, and alternatives are ranked with Fuzzy TOPSIS. Global robustness analysis, employing rank acceptability indices and structured stress-test scenarios, demonstrates that leading alternatives can exchange ranks under plausible uncertainty and that preferences may shift across regimes such as water scarcity or stricter acid mine drainage enforcement, supporting selection based on robustness and conditional optimality rather than a single deterministic ranking.
Exploitation
Amir Batarbiat; Mojtaba Rezakhah
Abstract
This study proposes an integrated optimization framework that simultaneously determines dynamic cut-off grades, stockpile management, and processing route selection to maximize the Net Present Value (NPV) of open-pit mining operations. Building upon Lane’s theory, the framework combines mathematical ...
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This study proposes an integrated optimization framework that simultaneously determines dynamic cut-off grades, stockpile management, and processing route selection to maximize the Net Present Value (NPV) of open-pit mining operations. Building upon Lane’s theory, the framework combines mathematical programming and dynamic optimization to model the complex interactions among mining, processing, and stockpiling decisions throughout the project lifecycle. The model is applied to a synthetic yet realistic benchmark case derived from a porphyry copper deposit, with minor data modifications to ensure confidentiality. Three alternative operating strategies are compared: a fixed cut-off grade policy, a dynamic cut-off grade policy, and a fully integrated dynamic policy incorporating strategic stockpiling. The integrated approach achieves the highest economic performance, yielding an NPV of $638.65 million—representing a 41% improvement over the fixed policy—while extending mine life to six years and increasing copper production to 115,787 tons. Sensitivity analysis confirms the strategy’s resilience to variations in costs and discount rates, as well as its responsiveness to metal price fluctuations, demonstrating its robustness and practical potential for strategic mine planning.
Environment
Masoud Monjezi; Safa Moezinia; Jafar Khademi Hamidi; Mojtaba Rezakhah; Vahid Amini; Amir Batarbiat
Abstract
Open-pit mine rehabilitation is essential for managing environmental impacts and achieving sustainable development after mining operations cease. The goal of this study is to find the best way to fix up the Zarshuran Gold Mine by ranking eight different ways to fix it up using the Fuzzy Analytic Hierarchy ...
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Open-pit mine rehabilitation is essential for managing environmental impacts and achieving sustainable development after mining operations cease. The goal of this study is to find the best way to fix up the Zarshuran Gold Mine by ranking eight different ways to fix it up using the Fuzzy Analytic Hierarchy Process (FAHP). These options are restoring the mine to its original state, planting trees, building a wind farm, creating a recreational area, setting up pastures, farming, building a solar power plant, and creating a tourist attraction. A panel of twelve experts evaluated these alternatives according to ten key criteria: air temperature intensity, number of sunny days, soil conditions, distance from residential areas, topographic irregularity, vegetation density, average wind speed, local animal species, site access, and the size and shape of the mined area. The results indicate that the construction of a solar power plant is identified as the most suitable rehabilitation option for the Zarshuran Gold Mine, considering the region’s climatic conditions (particularly the high number of sunny days per year) and its potential for clean energy generation and revenue creation. This study emphasizes the importance of considering environmental, social, and technical criteria in the decision-making process for mine rehabilitation and provides a framework for selecting sustainable rehabilitation methods in similar mining contexts.
Exploitation
Ali Nemati vardin; Masoud Monjezi; Hasel Amini Khoshalan; Jafar Hamidi Khademi; Mojtaba Rezakhah
Abstract
Drilling is one of the most important operations in open-pit mining, and the penetration rate of drill bits is a key performance measure. This paper presents research on the penetration rate of drill bits based on mining rock mass rating, thrust pressure (weight on bit), rotational pressure, and Schmidt ...
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Drilling is one of the most important operations in open-pit mining, and the penetration rate of drill bits is a key performance measure. This paper presents research on the penetration rate of drill bits based on mining rock mass rating, thrust pressure (weight on bit), rotational pressure, and Schmidt hammer rebound hardness. To achieve this, a dataset comprising the drilling operations of 85 blastholes from the Sungun copper mine in Iran was prepared and analyzed using statistical and intelligent methods. Multivariate regression analysis and artificial neural networks developed in Python, utilizing optimization algorithms such as gradient descent, stochastic gradient descent, and adaptive moment estimation, were applied to predict the penetration rate of drill bits in this study. The coefficient of determination (R²), mean absolute error (MAE), and root mean square error (RMSE) served as performance indicators to evaluate the methods employed. Among these, the adaptive moment estimation (Adam)-based model exhibited superior performance compared to alternative models, achieving values of R² = 0.96, MAE = 4.55, and RMSE = 4.30. Furthermore, the sensitivity analysis revealed that mining rock mass rating is the most influential factor on the rate of penetration, while thrust pressure has the least impact.
Exploitation
Mojtaba Rezakhah
Abstract
Optimizing short-term production in open-pit copper mines is crucial for maximizing economic returns and ensuring operational stability, yet is frequently challenged by inherent geological variability. This work presents a novel Mixed-Integer Linear Programming (MILP) framework designed to address these ...
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Optimizing short-term production in open-pit copper mines is crucial for maximizing economic returns and ensuring operational stability, yet is frequently challenged by inherent geological variability. This work presents a novel Mixed-Integer Linear Programming (MILP) framework designed to address these challenges by directly integrating critical geometallurgical parameters, specifically rock hardness (SPI index) and clay content, into the short-term production planning process. The simultaneous integration of these key geometallurgical feed quality attributes within an operational MILP model distinguishes this work from previous approaches and effectively bridges geological data analytics with operational decision-making, aligning economic objectives with enhanced metallurgical performance. Utilizing real operational data from the Sarcheshmeh Copper Mine, the framework was validated over a 186-day period. It achieved optimal production conditions on 137 days (73.6% of the duration), realizing a maximum Net Present Value (NPV) of $132,000. Key outcomes included a significant 21% reduction in concentrate grade variability and a 15% decrease in flotation reagent consumption, achieved through the simultaneous control of SPI and clay content. Advanced statistical methods were employed to identify critical relationships. While the model demonstrates scalability for porphyry copper mines globally, its successful implementation depends on careful parameter customization and alignment with existing infrastructure. This research work underscores the substantial value of data-driven, integrated optimization techniques in enhancing both profitability and process stability within mineral processing circuits.
Exploitation
Somaye Khajevand; Mojtaba Rezakhah; Masoud Monjezi; Fabián Alejandro Manríquez León
Abstract
Efficient loading and hauling systems, with trucks and shovels as the primary transportation machinery, are essential for optimizing mining operations. This study introduces a simulation-based approach to enhance the utilization of the hauling system in an Abbasbad copper mine in Iran. A dynamic truck ...
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Efficient loading and hauling systems, with trucks and shovels as the primary transportation machinery, are essential for optimizing mining operations. This study introduces a simulation-based approach to enhance the utilization of the hauling system in an Abbasbad copper mine in Iran. A dynamic truck allocation model is proposed to overcome the limitations of fixed allocation methods. In this approach, trucks are assigned to loading equipment based on the real-time throughput data, prioritizing equipment experiencing the highest production delays. The simulation results demonstrate that this flexible allocation model improves productivity, achieving a 13% increase in waste material handling compared to the fixed allocation scenario. These findings indicate that the proposed framework to significantly improve the efficiency and productivity of haulage systems in mining operations.
