Steady-State Optimization of Grinding Process

Considering the technologic traits of grinding processes,combining the concentrator mill production's output and quality,the multi-objective optimization problem of any grinding process is raised.To solve the problem of multi-objective optimization,a fast and outstanding multi-objective Genetic Algorithms NSGA-II(Non-dominated Sorting Genetic Algorithm II) was studied.The NSGA-II was improved in a selection of individuals before crossover.The filtering and restriction mechanism were introduced and simulation results show that the introduction of filtering and restriction mechanisms may limit the crossover of "near relative",maintaining the uniform distribution and diversity of the population.It may also accelerate the process to find the best sample.The improved NSGA-II was used for steady-state optimization of the grinding process.Many groups of suitable operating parameters of the actual production system can be found,and then the TOPSIS method can be used to select the optimal group of operating parameters.