Multiple criteria decision making (MCDM) is a supporting tool which is widely spread in different areas of science and industry. Many researchers have confirmed that MCDM methods can be useful for selecting the best solution in many different problems. In this paper, two novel methods are presented and applied on existing decision-making processes in the mining industry. The first method is multiple criteria ranking by alternative trace (MCRAT) and the second is ranking alternatives by perimeter similarity (RAPS). These two novel methods are demonstrated in decision-making problems and compared with the ranking of the same alternatives by other MCDM methods. The mining process often includes drilling and blasting operations as the most common activities for exploitation of raw materials. For optimal blasting design it is important to select the most suitable parameters for the blasting pattern and respect characteristics of the working environment and production conditions. By applying novel methods, how to successfully select the most proper blasting pattern respecting all conditions that must be satisfied for economic aspects and the safety of employees and the environment is presented.

Accurate metal price forecasting is the precondition for optimal and sustainable mine production planning. This paper combined two methods for time series analysis. The developed model represents the combination of the Grey System Theory and a Stochastic differential equation. More precisely, we added stochastic term to the first-order whitenization differential equation. Solution of this equation represents the time response function which is capable of creating artificial evolving paths of the metal price. The simulation process resulted in a distribution and adequate expected value at every single point. Further, model efficiency was increased by adding residuals modeled by the Singular Spectrum Analysis method. The model was tested on the monthly lead metal price series. Mean absolute percentage error is 4.37% and the model can be classified as a high-performance model.

The main aim of a coal deposit model is to provide an effective basis for mine production planning. The most applied approach is related to block modeling as a reasonable global representation of the coal deposit. By selection of adequate block size, deposits can be well represented. A block has a location in XYZ space and is characterized by adequate attributes obtained from drill holes data. From a technological point of view, i.e., a thermal power plant’s requirements, heating value, sulfur and ash content are the most important attributes of coal. Distribution of attributes’ values within a coal deposit can vary significantly over space and within each block as well. To decrease the uncertainty of attributes’ values within blocks the concept of fuzzy triangular numbers is applied. Production planning in such an environment is a very hard task, especially in the presence of requirements. Such requirements are considered as target values while the values of block attributes are the actual values. To make production planning easier we have developed a coal deposit model based on clustering the relative closeness of actual values to the target values. The relative closeness is obtained by the TOPSIS method while technological clusters are formed by fuzzy C-mean clustering. Coal deposits are thus represented by multi-attribute technological mining cuts.

In order to evaluate and control the seismic effect of blasting, as well as its planning, it is required to determine the soil oscillation law, with the strike/mining facilities to be protected. One of the most commonly used equations is that of M.A. Sadovskii, defining the law of alteration in the oscillation velocity of the soil depending on distance, the explosive amount, and conditions of blasting and geologic characteristics of the soil; all of this being determined on the basis of test blasting for the specific work environment. In the Sadovskii equation two parameters, K and n appear and they are conditioned both by rock mass characteristics and blasting conditions. The practical part of this study includes experimental investigations performed in the Veliki Krivelj Open Pit in the Bor District located in Eastern Serbia and investigations carried out during mass mining in the Kovilovača Open Pit near Despotovac, Eastern Serbia. Thus this paper offers several modes for determination of parameters K and n in the Sadovskii equation. To determine the parameters in the Sadovskii formula, in addition to the usual least square method, two more new models were applied. In the models the parameters K and n were determined by applying the quotient of the relative growth of oscillation velocities and reduced distances for Model 2. The link between the parameters K and n is determined by applying the trapezoidal formula for finding the value of definite integral for Model 3. In doing so, it was noted that all three models can be used to calculate the oscillation velocity of the rock mass.

Surface mining of coal has a negative impact on the environment that needs to be prevented, reduced, controlled, monitored by applying the management of technological processes of technical and biological recultivation after the end of exploitation works. The paper deals with the problem of multi-criteria decision-making in the process of selection of indicators that have an impact on the choice of purpose of recultivated terrain after the end of coal mining. The considered reclamation solutions represent possible alternatives. Degraded areas need to be returned to their original purpose, they should be in the function of environmental protection of the natural environment and settlements near this location. In addition, various criteria and sub-criteria that affect the choice of the most favourable solution were defined and analyzed. The final decision on land use after exploitation was made based on mathematical calculations using the multi-criteria VIKOR method.

The monitoring and analysis of concentrations of toxic metals (lead and cadmium) in soils and crops indicate that farmland in Serbia is generally not polluted, and the quality of soils is naturally good. Such soils are therefore suitable for organic farming. All noted instances of contamination by toxic metals are of a local nature only, and the result of fertilizers and pesticides, municipal waste, exhaust gases, nearby production facilities, smelting plants, mines, tailings ponds, etc. Locations of this type need to be monitored regularly, and the status of the soil and crops assessed. The results presented in this paper place special emphasis on lead and cadmium. In this regard, the sampling of 67 plant foodstuffs that are being grown in Baroševac village, located in the immediate vicinity of the Kolubara coal mine, was carried out. Fruit samples represented 14.9% and vegetable samples 85.1% of the total sample. The heavy metal content (lead/cadmium) in seven samples was above the limits prescribed by the Regulations. Overall exposure of the adult population of Baroševac, calculated on the basis of all samples (67 in total), was 0.89 µg lead per kg of body weight per week, representing only 3.5% provisional tolerable weekly intake (PTWI), and 0.46 cadmium per kg of body weight, which amounts to 6.7% PTWI. Both values point to the fact that the risk is low, even in the case of populations with high exposure to these toxic metals. This suggests that sustainable development may be possible in the near future.