ETD Collection

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Subject: search.filters.subject.Strip mining--Environmental aspects

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    Optimisation in open pit mining
    (2018) Phillips, Raymond
    The mining industry forms an integral part of South Africa - its society, culture, history and of course, its economy. This research dissertation focuses on the Open Pit Mine Production Scheduling Problem, a cornerstone in the design and planning of an open pit mining venture and its pro tability thereafter. The accompanying optimisation problem is usually both complex and large. We investigate existing initial solutions as well as two existing metaheuristic algorithms that have been used to solve this problem, improving upon them and introducing a pseudo greedy approach that seeks production schedule improvement in the immediate solution space neighbourhood. This addition greatly improves initial solutions to the problem. Through analysis on a smaller and larger mining instance we reveal the perceived advantages and disadvantages of two existing metaheuristics in producing optimal production schedules. We then propose a parent algorithm that interchangeably selects either of these algorithms based on probabilities determined by their observed performances during computation periods. The parent algorithm produces a strong production schedule that surpasses the current best found solution for the larger mining instance. With these ndings we propose a probabilistic selection method parent algorithm that interchanges between both algorithms in an e ort to achieve a better solution.
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    Assessing the impact of gold mining on the land use land cover change using GIS & Remote Sensing: case study in Yatela gold mine, Mali (1999-2015)
    (2017) Munyai, Vuledzani Hector
    The main purpose of this research was to investigate the impact of open pit mining on the Land Use Land Cover Change (LULCC) of the Yatela region in Mali. The methodology used to assess the open pit mining operations were remote sensing vegetation indices (NDVI) and LULC maps at a four year interval from 1999 to 2015. The Support Vector Machine (SVM) classification was used to create the LULC maps. Assessment of the quality from SVM classification outputs were analyzed using the confusion matrix technique. Three satellites (Landsat 5, 7 and 8) were used to analyze the images that were extracted from scene path 202 row 050. The NDVI results were able to detect the development and expenditure of the open pit mine in the Yatela region from 1999 to 2015. The roads and open pit mine area were easily detected from the 1999 NDVI results. Over the years the vegetation cover varied in the Yatela region, good vegetation cover was present before mine operations (1999) and after the mine closure (2015). The average overall accuracy for the five classified images was 84.31%. The change detection statistics showed that there were significant changes in each of the five classes over the 16 year period. Anthropogenic factors are assumed to be the major contributing factor to the Land Use Land Cover Change in the Yatela region. Nonetheless, this should not mean that climate factors can be neglected as contributing factors to LULCC in the region. Due to data limitation this research was unable to test any climatic influences.