Birinci M.Kumral M.Sarikaya M.2024-08-042024-08-0420099789944897150https://hdl.handle.net/11616/92378DEMIR EXPORT CO.21st International Mining Congress and Exhibition of Turkey, IMCET 2009 -- 6 May 2009 through 8 May 2009 -- 110207The design of a mineral processing plant dictates to determine optimal system parameters such as impeller speed, temperature, pH, process duration, solid % in pulp. The paper proposes a combination of multiple regression modelling and the multiobjective genetic algorithms (GA) to find the optimal system parameters simultaneously. In this research, impeller speed, process duration and solid % in pulp are considered as independent variables for the beneficiation of Al2O3 in pyrophyllite ore. Grade and electricity consumption are dependant variables. The multiple regression analysis is performed to relate dependant and independent variables to each other. The obtained models are used in optimisation procedure as objective functions. The first objective is to maximise the Al2O3 grade and the second one is to minimise electricity consumption. This is a multiobjective optimization problem and is solved by GA. The results showed that the proposed approach could be used to determine operation parameters in a mineral processing plant.eninfo:eu-repo/semantics/closedAccessAlgorithmsAluminumGenetic algorithmsImpellersMineralsMultiobjective optimizationOptimal systemsOptimizationRegression analysisSilicate mineralsElectricity-consumptionIndependent variablesMineral processing plantsMulti-objective genetic algorithmMulti-objective optimization problemMultiple regression analysisMultiple regression modellingOptimisation proceduresParameter estimationConference Object3833902-s2.0-84922932748N/A