Optimising the Loading System of Gol-e-Gohar Iron Ore Mine of Iran by Genetic Algorithm

In mining industries, materials handling costs represent a significant component of the operational cost. A variety of methods have been applied in surface mine equipment selection in order to select the suitable loading system with the lowest loading operation cost. These are queuing theory, bunching theory, linear programming and genetic algorithm. Among them, genetic algorithm is a simple method and applied for preliminary selection of the loading system. In this study, gathering information from anomaly No 2 of Gol-e-Gohar iron mine of Iran, loading system (number and its capacity) has been optimised by genetic algorithm. The study results showed that two shovels 8.25 m3 are required for the removal of 60 million tonnes of overburden. After removal overburden, these two shovels contribute to the extraction of 42 million tonnes of ore with a stripping ratio of 1:1.