Abstract
Silicon Dioxide (SiO2) is one of the most abundant minerals found on earth. SiO2 is widely used in various fields, so its availability as a finite natural resource diminishes. A purity procedure can raise the purity of low-quality silica by altering the temperature and rate of temperature rise. This study aims to obtain the best design for increasing SiO2 levels—the G-optimal design on a non-linear model using the Variable Neighborhood Search (VNS) algorithm. The VNS algorithm employs two types of neighborhoods, one acquired by replacing one design point with a candidate set and the other by replacing two design points with two points in the candidate set. The model used to increase silicon dioxide's purity is a non-linear model that follows the exponential decay distribution. The best design points obtained from the G-optimal design on the relationship between temperature (oC) and the rate of temperature increase (oC/min) 800 oC to 900 oC is a pair of points 800 oC and 1,67 oC /min, 800 oC and 2,17 oC/min, 815 oC and 2,50 oC/min, 825 oC and 2,00 oC/min, 845 oC and 2,34 oC/min, 895 oC and 3,34 oC/min 900 oC and 3,50 oC/min with a G-efficiency of 96,41%.
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