With production expansions, studies related to estimating the number of pieces of hauling equipment to be employed in open-pit mines have to be carried out. One of the main challenges comes from the methodology selected since numerous tools are available, including commercial solutions. However, given that some methodologies were complex or required an advanced understanding of programming languages and that, in the case study, the mining company was applying a deterministic approach, a stochastic methodology that involves a discrete-event simulation (DES) was proposed. Such an approach aimed to develop a calibration model whose inputs incorporated random variables, such as fixed times and tonnages loaded to hauling equipment. This model supported the replication of the yearly production plan for an open-pit copper mine in Peru located at 4500 masl that is expanding its operations in 2023 from 100,000 tons per day to 140,000. The results obtained from the stochastic methodology were compared with the deterministic approach, which showed that the stochastic model required additional trucks and that longer cycle times were generated from such an approach. Such outputs are now supporting engineers in anticipating future problems in the mine due to the generation of longer queues.

The semiarid areas of Manabí province in Ecuador are notably decertified due to overgrazing for animal production. In this study, a selection of the best alternative plants as food for livestock using the entropy-weight method, which is based on Shannon entropy theory, is developed. The entropy-weight method was applied to calculate the criteria weights; and then, the studied plants were ranked according to results of a pondered sum. The selection criteria were plant size (C1), dry material (C2), crude protein (C3), and crude fiber (C4). The possible plants were previously identified by their capacity to adapt to semiarid areas. The results shown that the best five plants were Anthyllis vulneraria, Imperta cylindrical, Cynodon plectostachyus, Bothriochloa pertusa, and Paspalidium desertorum, in that order. In the future, these selected plants could be cultivated experimentally; and then, according to the results, they could be considered as an alternative to resolve the food problem for livestock, or to recuperate the decertified areas in Manabí, Ecuador.

This article shows how to apply the Grey Clustering with Entropy Weight methodology for the calculation of a unified index of quality in distributed electricity, for which it is necessary to take measurements of electrical service quality parameters such as: the harmonic distortion rate in voltage and electric current, the Sag voltage, the deviation of the electrical frequency, the flickers and the power factor in the most important buses that are: Wind bus, PV/FC bus, Load bus, Grid bus. Finally, the measurements are grouped according to the use and non-use of compensation devices in the simulated power grid. This information becomes the input data for Grey Clustering with Entropy Weight, which allows for the calculation of the scores for each quality parameter. The valuations and measurements will allow for the calculation of the unified electric service quality index. Additionally, this research allows comparison with others that use the methodology of the hierarchical analytical process and for the same purpose and case study. Finally, the research allows the decision to be made on which distributed generation system option will be the most appropriate.

Social conflicts in the world have increased, due to the fact that the natural resources is being over exploited. In this work, we conducted a social conflict analysis using the entropy-weight method, which is based on Shannon entropy theory. The case study was conducted on a mining project allocated in northern Peru. The rural population and urban population stakeholder groups were analyzed under seven social criteria or variables. The results revealed that the criterion most likely to generate social conflict between stakeholder groups was access to drinking water. These results could help to central and local governments to make the best decision in order to prevent possible social conflict. The entropy-weight method showed interesting results and could be applied to other social conflicts, as this method considers the uncertainty within its analysis.