• an application of genetic algorithm method for optimization of the flotation column performance

    جزئیات بیشتر مقاله
    • تاریخ ارائه: 1392/07/24
    • تاریخ انتشار در تی پی بین: 1392/07/24
    • تعداد بازدید: 845
    • تعداد پرسش و پاسخ ها: 0
    • شماره تماس دبیرخانه رویداد: -
     the present work aims at employing genetic algorithms (gas) to optimize a pilot column flotation process. due to the high dimensionality and non-linearity of the model, the solution of the optimization problem through conventional algorithms does not always lead to convergence. to address this problem, the authors applied an evolutionary method, based on the gas, to deal with this process. in this way, in order to optimize the column flotation process, the ga is coupled with the mnlr of the column flotation metallurgical performance as fitness function. the aim of the optimization through gas is the searching for the process inputs that maximize the productivity (recovery and grade) of cooper in sarcheshme pilot plant. in this case, the simulation optimization problem is defined as finding the best values for the froth height, chemical reagent dosage, wash water and air flow rate, air holdup and cu grade in rougher and column feed streams. the results indicate that ga is a robust and powerful search method to find the best values of flotation column model parameters that lead to more reliable simulation predictions.

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