Optimization in mine planning could improve the economic benefit for mining companies. The main optimization contents in an underground mine includes stope layout, access layout and production scheduling. It is common to optimize each part sequentially, where optimal results from one phase are treated as the input for the next phase. The production schedule is based on the mining design. Access layout plays an important role in determining the connection relationships between stopes. This paper proposes a shortest-path search algorithm to design a network that automatically connects each stope. Access layout optimization is treated as a network flow problem. Stopes are viewed as nodes, and the roads between the stopes are regarded as edges. Moreover, the decline location influences the ore transport paths and haul distances. Tree diagrams of the ore transportation path are analyzed when each stope location is treated as an alternative decline location. The optimal decline location is chosen by an enumeration method. Then, Integer Programming (IP) is used to optimize the production scheduling process and maximize the Net Present Value (NPV). The extension sequence of access excavation and stope extraction is taken into account in the optimization model to balance access development and stope mining. These optimization models are validated in an application involving a hypothetical gold deposit, and the results demonstrate that the new approach can provide a more realistic solution compared with those of traditional approaches.

The main optimized objects in underground mines include: stope layout, access layout and production scheduling. It is common to optimize each component sequentially, where optimal results from one phase are regarded as the input data for the next phase. Numerous methods have been developed and implemented to achieve the optimal solution for each component. In fact, the interaction between different phases is ignored in the tradition optimization models which only get the suboptimal solution compared to the integrated optimization model. This paper proposes a simultaneous integrated optimization model to optimize the three components at the same time. The model not only optimizes the mining layout to maximize the Net Present Value (NPV), but also considers the extension sequence of stope extraction and access excavation. The production capacity and ore quality requirement are also taken into account to keep the mining process stable in all mine life. The model is validated to a gold deposit in China. A two-dimensional block model is built to do the resource estimation due to the clear boundary of the hanging wall and footwall. The thickness and accumulation of each block is estimated by Ordinary Kriging (OK). In addition, the conditional simulation method is utilized to generate a series of orebodies with equal possibility. The optimal solution of optimization model is carried out on each simulated orebody to evaluate the influence of geological uncertainty on the optimal mining design and production scheduling. The risk of grade uncertainty is quantified by the possibility of obtaining the expected NPV. The results indicate that the optimization model has the ability to produce an optimal solution that has a good performance under the uncertainty of grade variability.

One of the most critical aspects of mine design is to determine the optimum cut-off grade. Despite Lane’s theory, which aims to optimize the cut-off grade by maximizing the net present value (NPV), which is now an accepted principle used in open pit planning studies, it is less developed and applied in optimizing the cut-off grade for underground polymetallic mines than open pit mines, as optimization in underground polymetallic mines is more difficult. Since there is a similar potential for optimization between open pit mines and underground mines, this paper extends the utilization of Lane’s theory and proposes an optimization model of the cut-off grade applied to combined mining-mineral processing in underground mines with multi-metals. With the help of 3D visualization model of deposits and using the equivalent factors, the objective function is expressed as one variable function of the cut-off grade. Then, the curves of increment in present value versus the cut-off grade concerning different constraints of production capacities are constructed respectively, and the reasonable cut-off grade corresponding to each constraint is calculated by using the golden section search method. The defined criterion for the global optimization of the cut-off grade is determined by maximizing the overall marginal economics. An underground polymetallic copper deposit in Tibet is taken as an example to validate the proposed model in the case study. The results show that the overall optimum equivalent cut-off grade, 0.28%, improves NPV by RMB 170.2 million in comparison with the cut-off grade policy currently used. Thus, the application of the optimization model is conducive to achieving more satisfactory economic benefits under the premise of the rational utilization of mineral resources.

At present, with the increase of production capacity and the promotion of production, the reserves

of most mining enterprises under the original industrial indexes are rapidly consumed, and the full

use of low-grade resources is getting more and more attention. If mining enterprises want to make

full use of low-grade resources simultaneously and obtain good economic benefits to strengthening

the analysis and management of costs is necessary. For metal underground mines, with the gradual

implementation of exploration and mining projects, capital investment and labor consumption are

dynamic and increase cumulatively in stages. Consequently, in the evaluation of ore value, we should

proceed from a series of processes such as: exploration, mining, processing and the smelting of

geological resources, and then study the resources increment in different stages of production and the

processing. To achieve a phased assessment of the ore value and fine evaluation of the cost, based on

the value chain theory and referring to the modeling method of computer integrated manufacturing

open system architecture (CIMOSA), the analysis framework of gold mining enterprise value chain is

established based on the value chain theory from the three dimensions of value-added activities, value

subjects and value carriers. A value chain model using ore flow as the carrying body is built based on

Petri nets. With the CPN Tools emulation tool, the cycle simulation of the model is carry out by the

colored Petri nets, which contain a hierarchical structure. Taking a large-scale gold mining enterprise

as an example, the value chain model is quantified to simulate the ore value formation, flow, transmission

and implementation process. By analyzing the results of the simulation, the ore value at different

production stages is evaluated dynamically, and the cost is similarly analyzed in stages, which can improve mining enterprise cost management, promote the application of computer modeling and

simulation technology in mine engineering, more accurately evaluate the economic feasibility of ore

utilization, and provide the basis for the value evaluation and effective utilization of low-grade ores.

Overseas mining investment generally faces considerable risk due to a variety of complex risk factors. Therefore, indexes are often based on conditions of uncertainty and cannot be fully quantified. Guided by set pair analysis (SPA) theory, this study constructs a risk evaluation index system based on an analysis of the risk factors of overseas mining investment and determines the weights of factors using entropy weighting methods. In addition, this study constructs an identity-discrepancycontrary risk assessment model based on the 5-element connection number. Both the certainty and uncertainty of the various risks are treated uniformly in this model and it is possible to mathematically describe and quantitatively express complex system decisions to evaluate projects. Overseas mining investment risk and its changing trends are synthetically evaluated by calculating the adjacent connection number and analyzing the set pair potential. Using an actual overseas mining investment project as an example, the risk of overseas mining investment can be separated into five categories according to the risk field, and then the evaluation model is quantified and specific risk assessment results are obtained. Compared to the field investigation, the practicability and effectiveness of the evaluation method are illustrated. This new model combines static and dynamic factors and qualitative and quantitative information, which improves the reliability and accuracy of risk evaluation. Furthermore, this evaluation method can also be applied to other similar evaluations and has a certain scalability.

This paper researches the application of grey system theory in cost forecasting of the coal mine. The grey model (GM(1.1)) is widely used in forecasting in business and industrial systems with advantages of minimal data, a short time and little fluctuation. Also, the model fits exponentially with increasing data more precisely than other prediction techniques. However, the traditional GM(1.1) model suffers from the poor anti-interference ability. Aimed at the flaws of the conventional GM(1.1) model, this paper proposes a novel dynamic forecasting model with the theory of background value optimization and Fourier-series residual error correction based on the traditional GM(1.1) model. The new model applies the golden segmentation optimization method to optimize the background value and Fourier-series theory to extract periodic information in the grey forecasting model for correcting the residual error. In the proposed dynamic model, the newest data is gradually added while the oldest is removed from the original data sequence. To test the new model’s forecasting performance, it was applied to the prediction of unit costs in coal mining, and the results show that the prediction accuracy is improved compared with other grey forecasting models. The new model gives a MAPE & C value of 0.14% and 0.02, respectively, compared to 1.75% and 0.37 respectively for the traditional GM(1.1) model. Thus, the new GM(1.1) model proposed in this paper, with advantages of practical application and high accuracy, provides a new method for cost forecasting in coal mining, and then help decision makers to make more scientific decisions for the mining operation.

China has been building an ecological compensation system to eliminate the contradiction between economic development and ecological protection. Aiming at conflicts of interest in the implementation of an ecological compensation policy for China’s mineral resource development, this study established a tripartite evolutionary game model to simulate the ecological compensation scenario and determined the evolutionary stable strategy (ESS) under different scenarios; it uses numerical simulation to analyse the strategy evolution process of stakeholders and the influence of parameter changes on each strategy. The results show that there is an optimal ESS for ecological compensation for mineral resource development, which condition is C1 < Ti + F1, P < F2, C2 < R1 + R2. The initial cooperation intentions of stakeholders directly affected the final stable state. Local governments are most affected by the input cost, and mining enterprises are most affected by the supervision of the central government. Punishment can effectively restrain the behavior of local governments and mining enterprises and promote the implementation of ecological compensation systems. In addition, the higher supervision cost of the central government, the longer time it will take for the stakeholders to reach the stable state. Finally, reducing the payment amount for ecological compensation will not affect the trend in environmental improvement; in contrast, it is conducive to the preservation of enterprises’ strength, economic development and ecological environment protection. The main findings of this study can help secure coordinate between the stakeholders in conflict and jointly formulate appropriate ecological compensation policy.

The rapid development of the global economy has led to an increasing demand for resources. The disparity between the supply and demand of resources continues to be prominent and shows a situation of short supply. Resource investment projects with large amounts and long construction periods face many risks due to various unpredictable factors. Cultural, legal, economic and other environments vary between different countries. Therefore, comprehensive risk identification, understanding, evaluation, and analysis are important prerequisites for the success of mineral investment. In this paper, the risk of mineral resources investment in host countries is identified. A risk evaluation index system is established to objectively evaluate the risk environment of the host country. The risk evaluation index system includes four first-level indexes: political and legal risk, social and cultural risk, economic and financial risk, and natural risk. The subjective weight was determined by sending questionnaires to experts and scholars in the industry and conducting data processing. The entropy method was used to determine the objective weight. Finally, the subjective weight and the objective weight were combined to obtain a group of scientific and accurate combined weights. The matter-element theory was introduced into the cloud model and a risk assessment model based on the cloud matter-element theory was constructed with comprehensive consideration of the fuzziness and randomness of risks. Eight countries with relatively rich mineral resources were taken as cases to verify the model application. The research results provide a theoretical basis and decision-making methods for mineral enterprise investment.